Ultraviolet (UV) solar radiation causes multiple health detriments and materials degradation, these effects being strongly wavelength-dependent. Although coupled-charge device (CCD)-array spectrometers are an alternative to expensive and more labor-intensive scanning ones, they suffer from different sources of error, such as the dark signal and its Poisson noise associated, that must be previously characterized in depth to guarantee the quality of the measurements. This study proposes using the signal registered by the ghost pixels available in the instruments under study to estimate the dark signal. These ghost pixels are different from the known “blind pixels” since these ones register the dark signal, and the first ones were found to correspond to the output preamplifier offset. More than 7000 dark signal frames were measured at different temperatures and integration times for this study. The ghost-pixels signal was found to depend linearly on the temperature and be independent on the integration time, so it can be a proxy for temperature in dark signal correction models. To estimate the dark signal, several multivariate models dependent on the integration time and the ghost-pixels signal were tested. Finally, the best two, according to the Akaike information criterion (AIC), were selected. The chosen models perform notably well, with$R^{2}$values over 0.95 and low rRMSE values, below 25%. One of the ghost-pixels models chosen compares well with temperature-based models, although the latter show lower relative root mean squared error (rRMSE) values. This study presents the ghost-pixels signal as a reliable and efficient alternative to temperature measurements for models aimed at estimating the dark signal.

MOTIVATION: Molecular docking methods are extensively used to predict the interaction between protein-ligand systems in terms of structure and binding affinity, through the optimization of a physics-based scoring function. However, the computational requirements of these simulations grow exponentially with: (i) the global optimization procedure, (ii) the number and degrees of freedom of molecular conformations generated and (iii) the mathematical complexity of the scoring function. RESULTS: In this work, we introduce a novel molecular docking method named METADOCK 2, which incorporates several novel features, such as (i) a ligand-dependent blind docking approach that exhaustively scans the whole protein surface to detect novel allosteric sites, (ii) an optimization method to enable the use of a wide branch of metaheuristics and (iii) a heterogeneous implementation based on multicore CPUs and multiple graphics processing units. Two representative scoring functions implemented in METADOCK 2 are extensively evaluated in terms of computational performance and accuracy using several benchmarks (such as the well-known DUD) against AutoDock 4.2 and AutoDock Vina. Results place METADOCK 2 as an efficient and accurate docking methodology able to deal with complex systems where computational demands are staggering and which outperforms both AutoDock Vina and AutoDock 4. AVAILABILITY AND IMPLEMENTATION: https://[email protected]/Baldoimbernon/metadock_2.git. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Low-power wide-area network technologies allow sending sensor information through long distances with low data rates. Long Range (LoRa) is one of these technologies, which is less susceptible to noise and interference. This technology operates in unlicensed bands, increasing the chances of having interfering devices in the communication link. The issue of LoRa jamming with external interference and the effect of such interference in radio range has not been addressed in the literature. Therefore, tests measured packet loss, received signal strength, and signal-to-noise ratio with one end node located kilometers away from a gateway. Data were measured with and without external interference, to establish system robustness. This article computes an empirical model of the immunity region, where the level of interference does not affect LoRa communication. Results show that LoRa devices required interference levels up to 14 dBm to have total packet losses. These results are relevant for implementing LoRa systems, motivating researches to perform site surveys of interference and to account for range reduction in network design.

This paper focuses on the validation of the empirically corrected total ozone column (TOC) data provided by the Earth Probe Total Ozone Mapping Spectrometer (EP-TOMS) using ground-based measurements recorded by a well-calibrated Brewer spectroradiometer located at El Arenosillo (Spain). In addition, satellite TOC observations derived from the Ozone Monitoring Instrument (OMI) with the TOMS algorithm are also used in this paper. The agreement between EP-TOMS TOC data and Brewer measurements is excellent (R2~ 0.92) even for the period 2000-2005 when a higher EP-TOMS instrument degradation occurred. Despite its low magnitude, the EP-TOMS-Brewer relative differences depend on the solar zenith angle (SZA), showing a clear seasonal cycle with amplitude between ±2% and ±4%. Conversely, OMI-Brewer relative differences show a constant negative value around -1% with no significant dependence on SZA. No significant dependence on the ground-based to satellite-based differences with respect to the EP-TOMS scene or to the OMI crosstrack position is observed for either satellite retrieval algorithm. Finally, TOC, estimated by the two satellite instruments, have also been compared, showing a good agreement (R2~ 0.88). Overall, we conclude that the empirical correction of the EP-TOMS data record provides a reprocessed set of high quality. However, EP-TOMS data after year 2000 should not be used in calculations of global-ozone trending due to remaining errors in the data set and because it is no longer an independent data set.