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In this work, electrodes based on laser-scribed reduced graphene oxide were fabricated using filter paper as the substrate. To fabricate the electrodes, a water suspension of graphene oxide was filtered to produce a continuous and uniform film of graphene oxide on the filter paper surface. Subsequently, a CO2 laser was used to "write" the working, counter and reference eelctroes by reducing graphene oxide in specific areas to define complete sensors. Referecnce electrodes were then coated with a commercial Ag/AgCl conductive paste to produce a quasi Ag/AgCl reference. As fabricated devices were employed as electrochemical sensors for detection of phosphate ions in water by employing the molybdenum blue method. This method exploits the reaction between molybdate and phosphate ions in acidic media leading to a Keggin-type complex (PMo12O3 40) which, being electrochemically active, enables the indiret detection of phosphate ions. Sensors exhibited high selectivity and sensitive detection of phosphate ions in a wide linear range, from 1 to 20 & mu;M; with a limit of detection of 0.4 & mu;M. To demonstrate that sensors could be utilized for in-situ phosphate ion detection, paper substrate was first pre-loaded with sul-phuric acid and molybdate ions. During analysis, these chemicals were then desorbed directly into the test sample eliminating the need for any kind of external manipulation or reagent addition. Thus, this paper presents the fabrication of a portable, easy-to-use, biodegradable and fast phosphate ions sensor for in situ and real-time monitoring of water quality.

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.

Multilevel Power Inverters (MPIs) represent a valid solution to improve the performances of energy production systems from renewable energy sources. Furthermore, the use of novel FPGA control systems allows simplifying the implementation of multicarrier PWM techniques for MPIs with computational benefits. This paper describes the implementation of several multicarrier PWM techniques on NI-SOM sbRIO-9651 for the control of a three-phase five-level cascaded H-bridge inverter. In detail, sbRIO-9651 is a control system in the field of Power Electronics and Drives (PED) programmable in the LabVIEW graphical programming environment. The paper is focused on modulation techniques implementation, testing, and experimental validation.

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 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.

In this work, we have designed and realised a portable and compact electronic system for the synchronous acquisition of multiple physiological signals. The system employs a Texas Instruments ADS1298 front-end with 24-bit resolution for data acquisition and supports up to 8 channels and 4 kHz sampling rate. The front-end communicates via SPI with a STM32 microcontroller which pre-processes the data and sends them through USB or Bluetooth to a suitable PC application. The system has been realized for the simultaneous acquisition of electrocardiographic (ECG) and photoplethysmographic (PPG) signals, but it can also be employed for acquiring other typologies of signals, e.g. breathing or electro-dermal activity, for a potential use in the automotive field to assess the driver’s health status in real-time or, in perspective, the stress level. PPG probes have also been realised, each one including dual wavelength LED (emitting at 735 and 850 nm), and a Silicon Photomultiplier (SiPM) detector (provided by STMicroelectronics) having high responsivity and gain [1]. The system integrates an I2C interface, 8-channel, 16-levels current LED driver for PPG probes and includes a Graphical User Interface (GUI) able, in real time, to (i) plot the signals, (ii) save the data, (iii) calculate and display main cardiovascular parameters (i.e., heart rate, breath rate, pulse arrival time, pulse transit time, pulse wave velocity). Both instantaneous or averaged values of heart rate are shown, also to display the time variation of the considered parameters and thus assess the so-called Heart Rate Variability [2]. Current version of the system is able to acquire up to 5 PPG waveforms and 3 ECG leads. Figure 1 shows a photo of the system, alongside with the PPG probes (on the right) and the standard ECG electrodes (on the left) which are used for signals acquisition. Figure 2 illustrates some screenshots of the developed GUI showing 2 ECG leads and 2 PPG waveforms. In detail, Fig. 2(a) depicts the windows displaying the waveforms, while, Fig. 2(b) exhibits the window dedicated to show in real-time the instantaneous and averaged values of the above-mentioned physiological parameters. Several measurement campaigns have been carried out on healthy volunteers of different ages to both test the correct functioning of the system, and also to compare the Pulse Arrival Time values computed between different body locations. In the future, by performing measurements on other typologies of subjects (e.g., hypertensive or diabetic patients), a statistical analysis of the collected data will be carried out, in order to evaluate the capability of using our system for distinguishing between different pathologies or for early disease detection, or even for assessing various stress levels. This activity was supported by Advancing Smart Optical Imaging and Sensing for Health (ASTONISH) Project (Grant no. 692470), funded by H2020-EU.2.1.1.7.-ECSEL programme.

Network physiology is a recent approach describing the human body as an integrated network composed of several organ systems which continuously interact to produce healthy and diseased states. In this work, we apply the network physiology paradigm to study dynamical interactions between EEG activity and heart rate variability in children suffering from focal epilepsy. We aim to study the characteristics of brainheart coupling between, before, and after seizures to better understand the physiological mechanisms underlying seizure onset in the pre-ictal phase and the recovery of normal autonomic function in the post-ictal phase. In perspective, linking the dynamic information of brain-heart can provide useful information for a better seizure prediction. EEG and ECG data were recorded in 10 patients with focal epilepsy. After removal of baseline drift and muscle artifacts, the variability of heart rate and brain activity were measured extracting R-R intervals from the ECG and computing the spectral power of the EEG. 143 synchronous time series of 300 points were obtained in 4 different time windows (10 min and 10 sec before and after the seizure) and analyzed computing the cross-correlation coefficient (CC) and the mutual information (MI). A statistically significant increase of MI was observed just after seizure episodes (pvalue equal to 0.04, 10s before vs 10s after distributions, electrode O2), while a recovery of the baseline value was obtained 10 minutes after the episodes. This trend was found for several other EEG electrodes (Fp2, F3, F8, T3, C4, T4). On the contrary, CC did not change significantly across time windows. These results suggest that focal seizures are associated with an increased brain-heart coupling which is noticeable after seizure termination only in terms of mutual information. We conclude that focal epilepsy in childhood is associated with nonlinear brain-heart interaction mechanisms.

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.

This work presents a preliminary study on the electrical characterization of high efficiency bifacial solar cells. An opening discussion on the state-of-the-art of such advanced technology is initially proposed and the experimental characterization of some prototypes is described. From this analysis, it can be stated that the bifacial silicon solar cells can be a very promising technology with high electrical performances and efficiency.

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.

In this work, we analyze brain-heart interactions during different mental states computing mutual information (MI) between the dynamic activity of different physiological systems. In 18 healthy subjects monitored in a relaxed resting state and during a mental arithmetic and a serious game task, multichannel EEG, one lead ECG, respiration and blood volume pulse were collected via wireless non-invasive biosensors. From these signals, synchronous 300-second time series were extracted measuring brain activity via the δ, θ, α, and β EEG power, and activity of the body district via the ECG R-R interval η, the respiratory amplitude ϱ and the pulse arrival time π. MI was computed using a linear estimator: (i) between {η,ϱ,π} and {δ,θ,α,β}, to measure overall brain-body interactions; (ii) between each time series and the others of the same district, to measure information shared within a district; and (iii) between each time series of a district and all series of the other district, to evaluate individual contributions to the information shared between brain and body. Results document the existence of statistically significant brain-body interactions, with high MI values involving mainly the η body dynamics and the δ and β brain dynamics. State-dependent variations were mostly relevant to the MI of the brain system involving δ, θ, α during mental arithmetic, and α and β during serious game. Thus, MI can be useful to detect correlated activity within and between brain and body systems monitored simultaneously during different mental states.

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.

OBJECTIVE In this work we explore the potential of combining standard time and frequency domain indexes with novel information measures, to characterize pre- and post-ictal heart rate variability (HRV) in epileptic children, with the aim of differentiating focal and generalized epilepsy regarding the autonomic control mechanisms. APPROACH We analyze short-term HRV in 37 children suffering from generalized or focal epilepsy, monitored 10 s, 300 s, 600 s and 1800 s both before and after seizure episodes. Nine indexes are computed in time (mean, standard deviation of normal-to-normal intervals, root mean square of the successive differences (RMSSD)), frequency (low-to-high frequency power ratio LF/HF, normalized LF and HF power) and information (entropy, conditional entropy and self-entropy) domains. Focal and generalized epilepsy are compared through statistical analysis of the indexes and using linear discriminant analysis (LDA). MAIN RESULTS In children with focal epilepsy, early post-ictal phase is characterized by significant tachycardia, depressed HRV, increased LF power and LF/HF, and decreased complexity, progressively recovered across time windows after the episodes. Children with generalized seizures instead show significant tachycardia, lower RMSSD, higher LF power and LF/HF ratio before the seizure. These different behaviors are exploited by LDA analysis to separate focal and generalized epilepsy up to an accuracy of 75%. Results suggest a shift of the sympatho-vagal balance towards sympathetic dominance and vagal withdrawal, noticeable just after the termination of seizure episodes and then reverted in focal epilepsy, and persistent during inter-ictal and pre-ictal periods in generalized epilepsy. SIGNIFICANCE Our analysis helps in elucidating the pathophysiology of inter-ictal HRV autonomic control and the differential diagnosis of generalized and focal epilepsy. These findings may have clinical relevance since altered sympatho-vagal control can be related to a higher danger of morbidity and mortality, may reduce thresholds for life-threatening arrhythmias, and could be a biomarker of risk for sudden unexpected death in epilepsy.

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 this work, we present a series of measurements carried out on Ruthenium-based Dye Sensitized Solar Cells (DSSCs) after the application of different external electrical field values. Such measurements have been performed both in the dark and by illuminating the sample with sunlight emitted by a solar simulator (AM1.5G spectrum with a power irradiance of 1000 W/m2). Our results demonstrate that the initial electrical bias field modifies in both cases the behavior of the cell in terms of an anomalous improvement of the main electrical parameters.

This work focuses on the preparation of a piezoresistive sensor device, by exploiting an amphiphilic sample of graphene oxide (GO) as a compatibilizer for poly (lactic acid) (PLA)-Poly (ethylene-glycol) (PEG) blends. The presence of GO determined a high stiffening and strengthening effect, without affecting toughness, and allowed a good stability of mechanical properties up to 40 days. Moreover, GO endowed the materials with electrical properties highly sensitive to pressure and strain variations: the biodegradable pressure sensor showed a responsivity of 35 μA/MPa from 0.6 to 8.5 MPa, a responsivity around 19 μA/MPa from 8.5 to 25 MPa. For lower pressure values (around 0.16–0.45 MPa), instead, the responsivity increases up to 220 μA/MPa in terms of ΔI/ΔP (i.e. (ΔI/ΔI0)/P close to 1 kPa−1). Furthermore, this novel sensor is able to monitor submicrometric displacements with an impressive sensitivity (up to 25 μA/μm in terms of ΔI/ΔL, or 70 in terms of (ΔI/I0)/ε). We implemented a model able to predict pressure changes up to 25 MPa, by monitoring and measuring variations in electrical conductivity, thus paving the road to use these biodegradable, ecofriendly materials as low-cost sensors for a large pressure range.

The gold standard method to monitor heart rate variability (HRV) comprises measuring the time series of interbeat interval durations from electrocardiographic (ECG) recordings. However, due to the widespread use, simplicity and usability of photoplethysmographic (PPG) techniques, monitoring pulse rate variability (PRV) from pulse wave recordings has become a viable alternative to standard HRV analysis. The present study investigates the accuracy of PRV, measured as a surrogate of HRV, for the quantification of descriptive indexes computed in the time domain (mean, variance), frequency domain (low-to-high frequency power ratio LF/HF, HF band central frequency) and information domain (entropy, conditional entropy). We analyze short time series (300 intervals) of HRV measured from the ECG and of PRV acquired from Finometer device in 76 subjects monitored in the resting supine position (SU) and in the upright position during head-up tilt (HUT). Time, frequency and information domain indexes are computed for each HRV and PRV series and, for each index, the comparison between the two approaches is performed through statistical comparison of the distributions across subjects, robust linear regression, and Bland-Altman plots. Results of the comparison indicate an overall good agreement between PRV-based and HRV-based indexes, with an accuracy that is slightly lower during HUT than during SU, and for the band-power ratio and conditional entropy. These results suggest the feasibility of PRV-based assessment of HRV descriptive indexes, and suggest to further investigate the agreement in conditions of physiological stress.

In this work, we report on the electro-optical characterization of Dye Sensitized Solar Cells (DSSCs) which use ruthenium complexes as sensitizers. In particular, several kinds of measurements have been performed to study the electrical performances and the efficiency levels of the cells at different operating conditions. In detail, the measurements have been conducted at varying temperatures and hours of light soaking. Our results show that the short circuit current density J SC , the open circuit voltage V OC and the conversion efficiency η increase with the hours of light soaking, while they decrease with temperature. A thorough investigation on the light soaking process at the device level has been carried out, giving a wealth of experimental data which can be very useful to better single out and quantify the underlying physical phenomena and the effects on the cell parameters, which are still controversial among the scientific community. Finally, the ageing study demonstrates that the cell performance rapidly deteriorates in the first few months of exposure to light. All the obtained results are of great importance for a better understanding of the light soaking phenomenon and for improving the fabrication process of the DSSCs investigated during this study.

In this paper, we present an experimental investigation on the performance of Ruthenium-based Dye Sensitized Solar Cells (DSSCs) at different irradiance levels, incident wavelengths and hours of illumination. In particular, the measurements have been aimed at studying the performance variation due to light soaking effect since this phenomenon has noteworthy practical implications, such as stability tests of DSSCs. Our results show that the short circuit current density, the open circuit voltage and the conversion efficiency η increase with the hours of light soaking. Finally, the observed phenomenon is reversible, and thus the performance decreases again when the cell is kept in the dark.

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.

In this paper, we present an experimental comparison of two LiDAR systems, employing the SiPM and the APD as photodetectors, in terms of TOF measurements differing for the distance of the target and at different intensities of ambient light. The use of the APD represents the conventional approach, while the implementation of the SiPM is innovative. The performed measurements achieved very promising results, thus demonstrating the effectiveness of our LiDAR based on SiPM.

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.

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 this paper, we present an innovative way to measure some physiological parameters (such as the pre-ejection period, the pulse transit time, the blood pressure) in a cardiac cycle. A combo PPG-ECG system has been developed and employed to extract both the ECG signal from standard limb leads and simultaneously the photoplethysmography signal from the wrist and the forearm, to calculate the pre-ejection period. This system represents an easy and non-invasive technique to determine these biomedical parameters without using expensive impedance cardiography equipment.

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.

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%). © 2015 Antonino Parisi et al.

We performed a Signal to Noise Ratio characterization, in the continuous wave regime, at different bias voltages, frequencies and temperatures, on a novel 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 overall current flowing to the device. 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. Furthermore, Excess Noise Factor measurements of the SiPM, as a function of the applied bias, are shown and discussed. Our results show the outstanding performance of this novel class of SiPMs even without the need of any cooling system.

 Abstract— 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.

In this paper, a numerical analysis of relevant electrical parameters of multilayer structures for CIGS-based solar cells was carried out, employing the simulation software wxAMPS. In particular, we have focused on thin film cells having a ZnO:Al/ZnO/CdS/CIGS structure with a Molybdenum back contact. The aim of this work is to establish good theoretical reference values for an ongoing experimental activity, where our technology of choice is the single-step electrodeposition. In detail, we have analyzed how the main electrical properties change with the bang gap and the thickness of the absorber layer, for such a type of solar cell structure. Our results show that both efficiency and fill factor strongly depend on the energy gap. Instead, the absorber thickness plays a role up to a few microns, after which the cell parameters remain almost constant. As expected, the theoretical peak efficiency was found for a band gap value of 1.40 eV, corresponding to a Ga/(In+Ga) ratio of 0.66.

We report on our Signal-to-Noise Ratio (SNR) measurements carried out, in the continuous wave regime, at different frequencies and at various temperatures, on a novel class of silicon photomultipliers (SiPMs) fabricated in planar technology on silicon p-type substrate. SNR of SiPMs is given by the ratio of the photogenerated current, filtered and averaged by a lock-in amplifier, and the Root Mean Square (RMS) deviation of the same current. In our measurements, we have employed a 10 Hz equivalent noise bandwidth, around the lock-in amplifier reference frequency. The measured noise takes into account the shot noise, resulting from the photocurrent and the dark current, while background light is not present in our setup. We have found that the SNR is independent from frequency in the evaluated range 1 - 100 kHz. Our measurements highlight a quasi-flat trend of the SiPM SNR up to an overvoltage of about 5 V (with respect to the breakdown voltage of 28.0 V). At higher overvoltages (OV), we have observed a SNR decrease, mainly because of the strong increase of the shot noise. We have also performed a comparison between the SiPM and the PhotoMultiplier Tube (PMT) SNR as a function of the temperature of the SiPM package and at different bias voltages. Our results show the outstanding performance of this novel class of SiPMs even without the need of any cooling system. Indeed, their SNR is only a few dBs below the PMT SNR at room temperature. Furthermore, cooling the SiPM at a package cell temperature of 3 °C, it reaches the PMT SNR values at room temperature despite the SiPM is biased in the range 28.7 – 33.5 V, while the PMT has a bias value up to 950 V.

In this work, we have implemented a data recovery software integrating the most recent rateless codes, i.e., RaptorQ codes. Thanks to the above-mentioned software, it is possible to recover data loss occurring on several kinds of network conditions. We have performed a statistical analysis of failure probabilities at several configurations of RaptorQ parameters. We have found a good agreement with the theoretical values of a random linear fountain code over Galois Field GF(256). Moreover, we have shown that the probability of having a certain number of failed decoded source blocks - when sending a fixed size file - follows a Poisson distribution.

This paper analyzes how the electrical characteristics of a CIGS photovoltaic module are affected by the chemical composition and by the thickness variations of the CIGS absorber. The electrical characteristics here considered are the short circuit current, the open circuit voltage, the efficiency and the power peak. The chemical composition is varied by tuning the ratio between gallium and indium. This analysis has been performed by means of the wxAMPS software, developed by the University of Illinois. The above variations have been taken into account on a PV module made of 72 cells. This analysis has been carried out employing a PV module mathematical model developed and implemented by the Authors in Matlab environment.