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The weather-forecast based Radio Meteorological Operation Planner (RMOP) model for the dynamical link-budget design in satellite communications at Ka-band is described and validated. For the first time, actual received Ka-band data from a deep-space satellite mission (Hayabusa2 mission from JAXA and supported by ESA) were available for operational tests. RMOP-predicted link-budget parameters were delivered in real-time before each scheduled satellite transmission period. After each transmission, received data measured by the ground stations were exploited for the RMOP validation. The data-volume actually received (transmitted and lost) by Hayabusa2 was compared with the one that would have been obtained if the transmission had been configured according to RMOP predictions. The results prove that RMOP model is capable of receiving more than 100% of extra data-volume with respect to the classical link-budget design techniques while keeping data losses under control. A specific approach usable in case of rainy events is described, too. These outstanding results will pave the way to an operative use of the weather-forecast based RMOP model for future satellite missions. [ABSTRACT FROM AUTHOR]

The effective isotropic radiated power (EIRP) is a crucial parameter characterizing the transmitting antennas of a radio frequency satellite link. During the satellite commissioning phase, the requirements compliance of communication subsystems is tested. One of the required tests concerns the EIRP of the satellite transmitting antenna. Ground-based power measurements of the satellite-emitted signal are collected to measure EIRP, provided that an estimate of the atmospheric losses is available from independent ancillary measurements or model data. This article demonstrates the applicability of the so-called Langley method to infer EIRP and atmospheric attenuation simultaneously from ground-based power measurements, with no need for ancillary measurements. It is shown that the proposed method gives results similar to more traditional methods, without prior information on atmospheric attenuation. Thus, the proposed method can be applied to monitor EIRP throughout the satellite lifetime from ground-based power measurements alone. [ABSTRACT FROM AUTHOR]

An improved weather-forecast-based link-budget design technique for space-to-Earth links is described. The aim is the stochastic optimization of both transmission symbol rate and received signal-to-noise ratio. The proposed radiometeorological operations prediction (RadioMetOP) model takes into account the forecast uncertainty by a space–time ensemble method exploiting the temporal evolution of the predicted radiometeorological variables over the weather-forecast spatial grid. The unique possibility of testing and validating the RadioMetOP model is presented, thanks to the $Ka$ -band downlink measurements available from the support of the European Space Agency’s antenna tracking network to deep-space Hayabusa-2 (HB2) mission, operated by the Japan Aerospace Exploration Agency. First, the RadioMetOP model accuracy is tested by comparing the signal-to-noise ratio, measured during the transmission periods, with the simulated one, properly scaled to the symbol rate operated by HB2, finding correlation values of 0.9 that confirm the effectiveness of the proposed approach. Second, the $a$ posteriori analysis of the optimization process is accomplished, showing that depending on the considered criteria for the link-budget optimization, the use of the RadioMetOP model would have allowed a transmitted data volume more than doubled and an average signal-to-noise ratio gain between 2.1 and 3.8 dB. [ABSTRACT FROM AUTHOR]

The mean radiative temperature ($T_{mr}$) is a key function controlling the sky noise temperature in microwave receiving systems. A generalized parametric prediction (GPP) model of $T_{mr}$ for microwave slant paths in all-weather conditions is formulated and presented. The proposed GPP model is aimed at being multifrequency and surface-temperature scaled, valid for elevation angles from 5° to 90° and for frequencies ranging from 5 to 95 GHz within the three transmission windows delimited by the water vapor and the oxygen absorption peaks. The core of the GPP model is a parametrization driven by a physically based radiative transfer approach taking into account extinction, emission, and multiple scattering. The expression of $T_{mr}$ is normalized to the surface temperature of the considered site. The GPP model is verified with measurements available from the multiinstrument Italian Satellite (ITALSAT) campaign in Spino d’Adda, Milan, Italy, in 1994–1997, obtaining a fractional mean error ranging from 0.045 to 0.068. A comparison of the GPP model with the current ITU-R model shows a reduction in the root mean square error up to about 20 and 30 K, depending on the considered frequency. [ABSTRACT FROM AUTHOR]

The objective of this paper is to characterize the atmospheric radiometeorological parameters (optical thickness and brightness temperature) at centimeter and millimeter waves. To this aim, we have exploited two radiative transfer models (RTMs): a three-dimensional model (3D-RTM), driven by numerical weather forecasts, and a stochastic one-dimensional (1-D) model (1D-RTM), fed by a synthetic clouds dataset. We have compared the radiative transfer simulations with measurements from two ground-based microwave radiometers: a profiler and a Sun-tracking radiometer. The peculiarity of the latter is the capacity of simultaneously measuring atmospheric optical thickness and brightness temperature in all-weather conditions and at variable elevation angles. The comparisons between simulations and measurements provide satisfactory results that assess the reliability of the 3D-RTM with some biases, in terms of brightness temperature, that should be investigated. 3D-RTM turns out to be able to successfully reproduce correlations between brightness temperature and optical thickness and correlations among the different frequency channels. This confirms the potential of the combined use of weather forecast models and physically-based RTMs. On the other hand, 1D-RTM reveals to be able to reproduce frequency-channel correlation trends, but additional climatological set-up are needed to make the model exploitable for the computation of statistics of atmospheric optical thickness. These comparisons also highlight some possible calibration errors in the Sun-tracking radiometer that must be fixed. Finally, we have exploited measurements from the Sun-tracking radiometer to develop a model to retrieve the probability of atmospheric optical thickness conditioned to a given elevation angle. [ABSTRACT FROM AUTHOR]

Conducting polymer electrodes based on poly (3, 4 ethylenedioxythiophene):polystyrene sulfonate were used to record electrophysiological signals from autonomous cardiac contractile cells present in embryoid bodies. Signal detection was carried out by measuring the displacement current across the polymer/electrolyte double-layer capacitance, and compared with voltage detection. While for relatively low capacitance electrodes, the voltage amplification provides higher signal quality, and for high capacitive electrodes, the displacement current method exhibits a higher signal-to-noise ratio. It is proposed that the displacement current method combined with high capacitive polymer-based electrodes is adequate to measure clusters of cells and whole organs. Our approach has a great potential in fundamental studies of drug discovery and safety pharmacology. [ABSTRACT FROM PUBLISHER]

The aim of this paper is to investigate the usability of high-frequency channels for deep-space (DS) transmissions exploiting radiometeorological forecast modeling. A previously developed model chain for DS link-budget optimization, based on numerical weather forecasts (WFs), is adopted. The latter, already tested at Ka-band, exploits the combination of a high-resolution mesoscale forecast model and a radiative transfer model to predict the atmospheric scenario and optimize received data volume (DV) during DS transmissions. To shift available Ka-band results to other frequencies, we apply frequency-scaling laws to extrapolate forecast path attenuation, link parameters, and maximum allowed bit-rate for data transmission. Exploiting the available WF-based methodology, we compute DV return for DS missions operating at $X$ -, $K$ -, Ka-, $Q$ -, and $W$ -bands in order to make a comparative study of the behavior of DS transmission-channels at these frequencies. Results show that, in terms of received DV, an innovative WF-based approach is more convenient than traditional methodologies and exhibits a trend similar to the benchmark (ideal case). Increasing link frequency, received DV increases up to $Q$ -band. From $Q$ - to $W$ -band, despite received DV does not increase significantly, lost data remain under reasonable values, thus making the $W$ -band suitable if coupled with a WF-based technique. [ABSTRACT FROM AUTHOR]

The goal of this work is to demonstrate how the use of short-term radio-meteorological forecasts can aid the optimization of transferred data volumes from deep-space (DS) satellite payloads to Earth receiving stations. To this aim, a weather forecast (WF) numerical model is coupled with a microphysically oriented radiopropagation scheme in order to predict the atmospheric effects on Ka-band signals in DS links. A regional WFs model is exploited to obtain short-term predictions of the atmospheric state. The microphysically oriented radiopropagation scheme consists in a 3-D radiative transfer model which is used to compute the slant path attenuation and the antenna noise temperature at Ka-band in order to predict the signal-to-noise ratio at the receiving station. As a baseline, the BepiColombo mission to Mercury is chosen. Two prediction methods, statistical and maximization, are introduced and tested in two scenarios: 1) full-numerical scenario, where simulated data are used for evaluating the performances of the prediction techniques; 2) semiempirical scenario, where measured meteorological data are exploited to simulate beacon measurements in clear and rainy conditions. The results are shown in terms of received and lost data volumes and compared with benchmark scenarios. Using short-term radio-meteorological forecasts, yearly data volume return can be increased more than 20% if daily WFs, rather than monthly climatological statistics, are exploited. [ABSTRACT FROM AUTHOR]

A multilayer self-assembled monolayer (MuL-SAM) composed by i) cysteamine, ii) 4-formilphenyl boronic acid and iii) dopamine has been used to functionalize polycrystalline Au. Its electrochemical characterization shows how this surface engineering makes Au reactive toward dopamine. Kelvin probe measurements have shown how MuL-SAM tunes the surface potential of the bare Au. Such measurements are correlated with the electrical performances of organic field-effect transistors (OFETs), whose source/drain electrodes have been functionalized by MuL-SAM. Such devices, operated as charge-injection organic gauges (CIOGs), have shown sensitivity to the concentration of dopamine in the range of [1, 50] nM. [ABSTRACT FROM PUBLISHER]