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Despite the fact that the first red tide reported on the coasts of the Iberian Peninsula was due to Lingulodinium polyedra, knowledge about their frequency and, particularly, about the environmental conditions contributing to bloom initiation is still scarce. For this reason, L. polyedra bloom episodes were observed and studied in three Galician rias during the summer season based on the 1993–2008 record database period; additionally, samples were collected in summer 2008. Proliferations of L. polyedra occurred in the rias of Ares and Barqueiro in June and August, respectively, while in the Ria of Coruña, they persisted from the end of June to early September. Red tides developed when the surface temperature reached 17 °C, with “seasonal thermal window” conditions, and when salinities were ≥30, i.e., an “optimal salinity window”; when these parameters were lower than these thresholds, cyst germination decreased. A cyst transport mechanism from sediments to the surface must also exist; this mechanism was found to be natural (tidal currents) in the ria of Barqueiro or anthropogenic (dredging) in the rias of Ares and Coruña. Surface temperatures during summer were usually favorable for cyst germination (85 to 100%) during the 1993–2008 period; however, water temperatures below 10 m depth only rarely reached the 17 °C threshold (2 to 18%). During this 16-year period, dredging activities could explain 71% (Coruña) and 44% (Ares) of the recorded bloom events. When a bloom episode developed in early summer, favorable conditions did not lead to a new red tide, probably due to the lag period required by cysts for germination. Moreover, blooms did not develop when high densities of diatoms (>1,000,000 cells·L−1) remained in the water column as a result of summer upwelling pulses occurring in specific years. The temperature–sediment disturbance pattern found in this study provides a useful tool for the prevention of eventual risks resulting from red tides of this dinoflagellate.

Body temperature is usually employed in clinical practice by strict binary thresholding, aiming to classify patients as having fever or not. In the last years, other approaches based on the continuous analysis of body temperature time series have emerged. These are not only based on absolute thresholds but also on patterns and temporal dynamics of these time series, thus providing promising tools for early diagnosis. The present study applies three time series entropy calculation methods (Slope Entropy, Approximate Entropy, and Sample Entropy) to body temperature records of patients with bacterial infections and other causes of fever in search of possible differences that could be exploited for automatic classification. In the comparative analysis, Slope Entropy proved to be a stable and robust method that could bring higher sensitivity to the realm of entropy tools applied in this context of clinical thermometry. This method was able to find statistically significant differences between the two classes analyzed in all experiments, with sensitivity and specificity above 70% in most cases.

Many entropy-related methods for signal classification have been proposed and exploited successfully in the last several decades. However, it is sometimes difficult to find the optimal measure and the optimal parameter configuration for a specific purpose or context. Suboptimal settings may therefore produce subpar results and not even reach the desired level of significance. In order to increase the signal classification accuracy in these suboptimal situations, this paper proposes statistical models created with uncorrelated measures that exploit the possible synergies between them. The methods employed are permutation entropy (PE), approximate entropy (ApEn), and sample entropy (SampEn). Since PE is based on subpattern ordinal differences, whereas ApEn and SampEn are based on subpattern amplitude differences, we hypothesized that a combination of PE with another method would enhance the individual performance of any of them. The dataset was composed of body temperature records, for which we did not obtain a classification accuracy above 80% with a single measure, in this study or even in previous studies. The results confirmed that the classification accuracy rose up to 90% when combining PE and ApEn with a logistic model.

We describe a device for dual channel body temperature monitoring. The device can operate as a real time monitor or as a data logger, and has Bluetooth capabilities to enable for wireless data download to the computer used for data analysis. The proposed device is capable of sampling temperature at a rate of 1 sample per minute with a resolution of 0.01 °C. The internal memory allows for stand-alone data logging of up to 10 days. The device has a battery life of 50 hours in continuous real-time mode. In addition to describing the proposed device in detail, we report the results of a statistical analysis conducted to assess its accuracy and reproducibility.

Outpatient parenteral antimicrobial therapy (OPAT) with continuous infusion pumps is postulated as a very promising solution to treat complicated infections, such as endocarditis or osteomyelitis, that require patients to stay in hospital during extended periods of time, thus reducing their quality of life and increasing the risk of complications. However, stability studies of drugs in elastomeric devices are scarce, which limits their use in OPAT. Therefore, we evaluated the stability of ampicillin in sodium chloride 0.9% at two different concentrations, 50 and 15 mg/mL, in an elastomeric infusion pump when stored in the refrigerator and subsequently in real-life conditions at two different temperatures, 25 and 32 °C, with and without the use of a cooling device. The 15 mg/mL ampicillin is stable for up to 72 h under refrigeration, allowing subsequent dosing at 25 °C for 24 h with and without a cooling device, but at 32 °C its concentration drops below 90% after 8 h. In contrast, 50 mg/mL ampicillin only remains stable for the first 24 h under refrigeration, and subsequent administration at room temperature is not possible, even with the use of a cooling system. Our data support that 15 mg/mL AMP is suitable for use in OPAT if the volume and rate of infusion are tailored to the dosage needs of antimicrobial treatments.