The application of near infrared (NIR) spectroscopy for industrial process monitoring is achieving increasing importance over the last twenty years. In fact, the real time monitoring capacity of NIR spectroscopy is a very important feature for process monitoring, prediction and control as it allows a fast evaluation of the state of the process. However, the application of NIR spectroscopy in wastewater treatment processes is still to be explored. Although some applications of the technique for wastewater monitoring have been reported in the literature, there is still a need for more investigation related with applications, limitations and advantages of the technique when compared with other methods. An activated sludge reactor for aerobic treatment of a complex medium was monitored in situ with a NIR transflectance probe and traditional chemical parameters analysed off-line. NIR spectrophotometric data measured at the feed, reactor and settler were coupled to principal component analysis (PCA) to infer about the ability of this monitoring system to detect changes in the feed influent. The analysis of the score plots resulting from PCA permitted to identify the moments at which the perturbations occurred and to follow the consequent instability induced in the reactor till the day where the system is recuperated. The promising results obtained, suggest the interest in more detailed studies on the feasibility of NIR spectroscopy as an alternative method for monitoring and control of wastewater treatment processes.

The application of near infrared (NIR) spectroscopy for industrial process monitoring is achieving increasing importance over the last twenty years. In fact, the real time monitoring capacity of NIR spectroscopy is a very important feature for process monitoring, prediction and control as it allows a fast evaluation of the state of the process. However, the application of NIR spectroscopy in wastewater treatment processes is still to be explored. Although some applications of the technique for wastewater monitoring have been reported in the literature, there is still a need for more investigation related with applications, limitations and advantages of the technique when compared with other methods. An activated sludge reactor for aerobic treatment of a complex medium was monitored in situ with a NIR transflectance probe and traditional chemical parameters analysed off-line. NIR spectrophotometric data measured at the feed, reactor and settler were coupled to principal component analysis (PCA) to infer about the ability of this monitoring system to detect changes in the feed influent. The analysis of the score plots resulting from PCA permitted to identify the moments at which the perturbations occurred and to follow the consequent instability induced in the reactor till the day where the system is recuperated. The promising results obtained, suggest the interest in more detailed studies on the feasibility of NIR spectroscopy as an alternative method for monitoring and control of wastewater treatment processes.

Despite the accumulated knowledge on moral decision-making in the early stages of development, empirical evidence is still limited in the old-aged adults. The current study contributes to unveil the neural correlates of judgments of moral transgressions as a function of aging, by examining the temporal dynamics of neural activation elicited by intentional and accidental harmful actions in three groups of healthy participants: young adults (18-35), adults (40-55), and older adults (60-75). Older adults were slower and less accurate in rating intentionality, compared to the younger groups. In ERP analysis, the older group showed increased P2 amplitude, which was predicted by poorer performance on neuropsychological tests. Reduced amplitudes were found on critical ERP components to moral cognition (N2 and LPP), namely while processing intentional harmful scenarios. Older adults seem to allocate more attentional resources (P2) to the task, probably to compensate the age-related decline in executive functioning, while younger groups show a pronounced negativity while detecting harm (N2) and increased neural activation to encode the intentions behind the acts (LPP).

The valorization of glycerol wastes through its conversion into high-added value products using biotechnological processes is very promising due to the high amount of glycerol generated from the bio-diesel industry. In this sense, it is important to develop rapid, reliable and, if possible, environmentally friendly analytical techniques for the monitoring of high-added value compounds. With this in mind, Fourier transform near infrared (FT-NIR) spectroscopy was explored for the assessment of biomass, glycerol, l-phenylalanine and 2-phenylethanol (2-PE) parameters during the biotechnological production of 2-PE. A total of 80 samples were collected and analyzed through FT-NIR spectroscopy. Partial least squares (PLS) regression method was selected for establishing quantification models. The obtained figures of merit, in terms of, coefficients of determination of prediction (R2P), range error-ratios (RER) and residual predictive deviation (RPD) yielded values higher than 0.85, 7.7 and 2.6, respectively, for all the parameters assessed. The obtained results reveal that all the developed PLS models can be considered as models with a good predictive accuracy and therefore attest the suitability of FT-NIR spectroscopy for the quantification of these parameters. Concluding, a new rapid, reliable, cost-effective, accurate, multi-parametric and environmentally friendly analytical technique exploring the potential of FT-NIR spectroscopy was successfully developed.

Background: Previous studies have demonstrated the feasibility of using an asthma app to support medication management and adherence but failed to compare with other measures currently used in clinical practice. However, in a clinical setting, any additional adherence measurement must be evaluated in the context of both the patient and physician perspectives so that it can also help improve the process of shared decision making. Thus, we aimed to compare different measures of adherence to asthma control inhalers in clinical practice, namely through an app, patient self-report and physician assessment. Methods: This study is a secondary analysis of three prospective multicentre observational studies with patients (≥13 years old) with persistent asthma recruited from 61 primary and secondary care centres in Portugal. Patients were invited to use the InspirerMundi app and register their inhaled medication. Adherence was measured by the app as the number of doses taken divided by the number of doses scheduled each day and two time points were considered for analysis: 1-week and 1-month. At baseline, patients and physicians independently assessed adherence to asthma control inhalers during the previous week using a Visual Analogue Scale (VAS 0-100). Results: A total of 193 patients (72% female; median [P25-P75] age 28 [19-41] years old) were included in the analysis. Adherence measured by the app was lower (1 week: 31 [0-71]%; 1 month: 18 [0-48]%) than patient self-report (80 [60-95]) and physician assessment (82 [51-94]) (p < 0.001). A negligible non-significant correlation was found between the app and subjective measurements (ρ 0.118-0.156, p > 0.05). There was a moderate correlation between patient self-report and physician assessment (ρ = 0.596, p < 0.001). Conclusions: Adherence measured by the app was lower than that reported by the patient or the physician. This was expected as objective measurements are commonly lower than subjective evaluations, which tend to overestimate adherence. Nevertheless, the low adherence measured by the app may also be influenced by the use of the app itself and this needs to be considered in future studies.