Investigating aggregation in ice and snow clouds using novel combination of triple-frequency cloud radars and radar Doppler spectra

Clouds are essential component of the hydrological cycle for transporting of water and distributing precipitation at different parts of the planet. On a global scale, around 63% of the precipitation originates via ice phase. Different ice microphysical processes can lead to growth (e.g. deposition, aggregation, riming) or reduction (e.g. sublimation, breakup) of ice particle sizes. Aggregation, in particular, rapidly increases ice particles sizes and continuously changes the particle size distribution. However, aggregation and other ice microphysical processes are not fully understood. In order to improve the current knowledge about aggregation and the other microphysical processes, microwave radars are used to observe clouds due to their capability of retrieving information through the different parts of the clouds. Additionally, if Doppler radars operating at different frequencies (multi-frequency setup) are used to observe the same region of clouds, the multi-frequency observations can be used to retrieve information of particles sizes and velocities. This thesis uses multi-frequency Doppler observations (6 months) to investigate scenarios that intensify aggregation and the impact of increasing aggregate sizes on raindrop sizes. To this end, a multi-frequency data processing framework is introduced to minimize the effect of attenuation (e.g. atmospheric gases, snow, wet radome) and radar miscalibration; it also assigns a set of quality flags to the different correction steps. The statistical analysis from the observations of the ice part of the clouds indicates that aggregation is intensified in two temperature regions. The first region is between -20 and -10 °C and coincides with the dendritic growth zone (DGZ). Dendritic crystals can favour aggregation due to their branched structure. In addition to the growth of dendrites, the statistical results suggest that an intensification of aggregation in this temperature region correlates with an intensification of updrafts (up to 0.3 m/s). The statistics also show that approximately 25% of the cases where aggregation intensifies an additional mode of small and slow falling particles are present. The temperature region between -10 and 0 °C coincides with the region where the stickiness of ice surfaces increases due to the effect of a quasi liquid layer on the ice surface. Due to this increased stickiness, aggregation intensifies towards the 0 °C isotherm. The statistical results indicate that the growth of large aggregates in the DGZ favour, but it is not sufficient to guarantee the presence of even larger aggregates close to 0 °C. The results also indicate that an increase in aggregate sizes close to the 0 °C correlates with an increase in raindrop sizes. The multi-frequency processing framework and the other filtering processes introduced in this thesis can be used as the foundations for future multi-frequency experiments. The highly qualified multi-frequency dataset and the statistical results from this thesis can be used to evaluate the ice microphysical processes implemented in numerical models

A procedure for testing the quality of LANDSAT atmospheric correction algorithms

There are two basic methods for testing the quality of an algorithm to minimize atmospheric effects on LANDSAT imagery: (1) test the results a posteriori, using ground truth or control points; (2) use a method based on image data plus estimation of additional ground and/or atmospheric parameters. A procedure based on the second method is described. In order to select the parameters, initially the image contrast is examined for a series of parameter combinations. The contrast improves for better corrections. In addition the correlation coefficient between two subimages, taken at different times, of the same scene is used for parameter's selection. The regions to be correlated should not have changed considerably in time. A few examples using this proposed procedure are presented

Mental health literacy regarding depression and suicide.

Introduction: Mental health literacy enables individuals to recognize the symptoms associated with mental illness, and thus adjust their behavior to manage and seek help and treatment for mental illness. Aims: The present research aims to study determinants of mental health literacy and whether an association exists between mental health literacy and the understanding of content related to depression and suicide. Methods: In each group, the participants read one leaflet about depression or suicide and answered a questionnaire to assess their understanding. All the participants also filled out a mental health literacy self-report. Results: The results showed higher mental health literacy for women and individuals with a higher education. Mental health literacy predicted the understanding of suicide content, but the same did not apply for depression. Conclusions: Mental health literacy stands as an important factor to be considered in developing campaigns and promotional actions. However, its effect remains contingent on the contents and context. It is crucial to consider this interaction in maximizing the campaigns’ impact on the population.info:eu-repo/semantics/publishedVersio

New approach to predict shear capacity of reinforced concrete beams strengthened with NSM technique

Understanding the shear behavior of a concrete beam is still a challenging task due to several complex mechanisms involved. The Modified Compression Field Theory (MCFT) demonstrated an ability to predict, with good accuracy, the shear capacity of reinforced concrete (RC) members. Due to its iterative nature, the MCFT is not a straightforward design methodology, and a simplified MCFT (SMCFT) approach of this method was proposed to overcome this aspect. This model takes into account the tensile stress installed in the cracked concrete and inclination of the diagonal compressive strut, and requires a smaller number of model parameters than MCFT. This paper presents a new approach to predict the shear capacity of RC beams shear strengthened with fiber-reinforced polymer (FRP) laminates/rods applied according to the near-surface-mounted (NSM) technique. The new approach is based on the SMCFT and considers the relevant features of the interaction between NSM FRP systems and surrounding concrete, such as debonding of FRP laminate/rod and fracture of surrounding concrete of FRP. The experimental results of 100 beams strengthened with different configurations and shear strengthening ratio of FRP reinforcements are used to appraise the predictive performance of the developed approach. By evaluating the ratio between the experimental results to the analytical predictions (Vexp./Vana.), an average value of 1.09 is obtained for the developed approach with a coefficient of variation of 11%.The study presented in this paper is a part of the research project 38780, QREN, titled “CutInov – Innovative carbon fibre reinforced polymer laminates with capacity for a simultaneous flexural and shear/punching strengthening of reinforced concrete elements”, co-financed by the European Regional Development Fund (FEDER) through the Operational Program COMPETE. The first author acknowledges the research grant provided by this project.info:eu-repo/semantics/publishedVersio

Understanding differential stress and mental health reactions to COVID-19 related events

The effects of the pandemic on mental health can be studied through different variables, such as the number of COVID-19 stressors, the stressor types, and the stress responses. Understanding the sources of mental strain is crucial for developing effective interventions. The present study analyzed the relationship between these COVID-19-related variables and positive and negative mental health. A cross-sectional study was conducted with 666 individuals from the Portuguese general population, mostly females (65.5%) between 16–93 years old. They completed self-report measures regarding the number of COVID-19 stressors, the stressor types, the stress responses (IES-R), and positive (MHC-SF) and negative mental health (BSI-18). The results demonstrated that a higher number of COVID-19-experienced stressors and more stress responses were related to worse mental health. Regarding stressor types, experiences not related to the COVID-19 infection (e.g., tension at home) presented the largest effects on mental health. The strongest predictor was the stress responses for negative (β = 0.50) and positive mental health (β = −0.17). The predictors explained more about negative mental health than positive. These findings support the idea that individual appraisals play a crucial role in mental health.Fundação para a Ciência e Tecnologia - FCTinfo:eu-repo/semantics/publishedVersio