Hopes and fears of first-year freshman college students during the COVID-19 pandemic

The COVID-19 pandemic made the experience of being a first-year freshman college student unique. This study aims to analyze the hopes and fears of these students concerning their current life and future goals. Participating students completed the Hopes & Fears questionnaire. Results showed that students’ hopes and fears were mainly connected with domains of education and the global/collective dimension, followed by personal and family members’ health. Two new categories emerged, self-fulfillment and solidarity, reflecting the importance of the contextual dimension that these students were navigating. The findings of the current study contribute to the research of college students’ hopes and fears towards their future and accounts for the analyses of this topic as we progress to a post-pandemic phase

Analysis and Inter-Calibration of Wet Path Delay Datasets to Compute the Wet Tropospheric Correction for CryoSat-2 over Ocean

Unlike most altimetric missions, CryoSat-2 is not equipped with an onboard microwave radiometer (MWR) to provide wet tropospheric correction (WTC) to radar altimeter measurements, thus, relying on a model-based one provided by the European Center for Medium-range Weather Forecasts (ECMWF). In the ambit of ESA funded project CP4O, an improved WTC for CryoSat-2 data over ocean is under development, based on a data combination algorithm (DComb) through objective analysis of WTC values derived from all existing global-scale data types. The scope of this study is the analysis and inter-calibration of the large dataset of total column water vapor (TCWV) products from scanning MWR aboard Remote Sensing (RS) missions for use in the WTC computation for CryoSat-2. The main issues regarding the computation of the WTC from all TCWV products are discussed. The analysis of the orbital parameters of CryoSat-2 and all other considered RS missions, their sensor characteristics and inter-calibration is presented, providing an insight into the expected impact of these datasets on the WTC estimation. The most suitable approach for calculating the WTC from TCWV is investigated. For this type of application, after calibration with respect to an appropriate reference, two approaches were found to give very similar results, with root mean square differences of 2 mm

Cured database of sustained speech parameters for chronic laryngitis pathology

This paper reports the construction and organization of a database of speech parameters extracted from a speech sound database. The database is freely available on internet and the paper intends also theirs advertise for the research community. The database includes the parameters extracted from the sound of sustained vowels produced by a group of Chronic Laryngitis patients and a group of control subjects with similar characteristics concerning gender and age. The set of parameters of this database consists in the Jitter, Shimmer, Harmonic to Noise Ratio (HNR), Noise to Harmonic Ratio (NHR) and Autocorrelation extracted from the sound of sustained vowels /a/, /i/ and /u/ at low, neutral and high tones.info:eu-repo/semantics/publishedVersio

Acoustic analysis of chronic laryngitis - statistical analysis of sustained speech parameters

This paper describes the statistical analysis of a set of features extracted from the speech of sustained vowels of patients with chronic laryngitis and control subjects. The idea is to identify which features can be useful in a classification intelligent system to discriminate between pathologic and healthy voices. The set of features analysed consist in the Jitter, Shimmer Harmonic to Noise Ratio (HNR), Noise to Harmonic Ratio (NHR) and Autocorrelation extracted from the sound of a sustained vowels /a/, /i/ and /u/ in a low, neutral and high tones. The results showed that besides the absolute Jitter, no statistical significance exist between male and female voices, considering the classification between pathologic or healthy. Any of the analysed parameters is likely to be a statistical difference between control and Chronic Laryngitis groups. This is an important information that these features can be used in an intelligent system to classify healthy from Chronic Laryngitis voices.info:eu-repo/semantics/publishedVersio

Atmospheric plasma and UV polymerisation for developing sustainable anti-adhesive polyethylene terephthalate (PET) surfaces

Enhancing the hydrophilicity of polymeric materials is an important step for achieving anti-adhesiveness. Thus, in this study, atmospheric plasma as a pre-treatment was combined with a UV grafting process to obtain a durable surface modification on polyethylene terephthalate (PET). The most promising conditions for the atmospheric plasma process were found to be 15 kW power and 4 m/min speed, leading to a contact angle reduction from 70 ± 6° to approximately 30°. However, it was observed that these values increased over time due to the ageing and washing of the PET surface, ultimately causing it to recover its initial contact angle. Therefore, the plasma-pre-treated PET samples were further modified through a UV grafting process using sodium acrylate (NaAc) and 3-sulfopropyl acrylate potassium salts (KAc). The grafted acrylate PET samples exhibited contact angles of 8 ± 3° and 28 ± 13° for NaAc and KAc, respectively, while showing durability in ageing and washing tests. The dry film thicknesses for both samples were found to be 28 ± 2 μm. Finally, the anti-adhesive properties of the NaAc- and KAc-treated surfaces were evaluated using an Escherichia coli expressing YadA, an adhesive protein from Yersinia. The modified PET surfaces were highly effective in reducing bacterial adhesion by more than 90%.This work was supported by the ViBrANT project, which received funding from the EU Horizon 2020 Research and Innovation Programme under Marie Sklowdowska-Curie (grant agreement no. 765042), and the Portuguese Foundation for Science and Technology (FCT) (grant number UIDB/04469/2020).info:eu-repo/semantics/publishedVersio

A longitudinal study on maternal depressive symptoms during the COVID-19 pandemic: the role of strict lockdown measures and social support

Objectives: This study examined the trajectory of perinatal depressive symptoms in Portuguese women during the COVID-19 pandemic and the role of individual, relational, and contextual risk and protective factors. Methods: This 3-wave longitudinal study followed 290 pregnant women from the third trimester of pregnancy until 6-months postpartum. Women self-reported on depressive symptoms, psychological (anxiety, perceived stress, mindfulness), relational (perceived social support, dyadic adjustment, sexual wellbeing), and contextual (lockdown status) factors. Results: Women who were under strict lockdown presented significantly higher scores of depressive symptoms at baseline (by 1.38 EPDS points) than women who were not under strict lockdown measures. Mixed Growth Models showed that trajectories of depressive symptoms were explained by differences in women’s baseline depression. Differences in women’s depressive symptoms at baseline were mainly explained by higher anxiety and lower social support (22% and 24% for women under lockdown; 39% and 6% for women not on lockdown, respectively). Conclusion: Preventative interventions targeted at pregnant women should aim to reduce anxiety and enhance women’s social support to prevent depression in pregnancy and postpartum during the COVID-19 pandemic

Can superhydrophobic PET surfaces prevent bacterial adhesion?

Prevention of bacterial adhesion is a way to reduce and/or avoid biofilm formation, thus restraining its associated infections. The development of repellent anti-adhesive surfaces, such as superhydrophobic surfaces, can be a strategy to avoid bacterial adhesion. In this study, a polyethylene terephthalate (PET) film was modified by in situ growth of silica nanoparticles (NPs) to create a rough surface. The surface was further modified with fluorinated carbon chains to increase its hydrophobicity. The modified PET surfaces presented a pronounced superhydrophobic character, showing a water contact angle of 156° and a roughness of 104 nm (a considerable increase comparing with the 69° and 4.8 nm obtained for the untreated PET). Scanning Electron Microscopy was used to evaluate the modified surfaces morphology, further confirming its successful modification with nanoparticles. Additionally, a bacterial adhesion assay using an Escherichia coli expressing YadA, an adhesive protein from Yersinia so-called Yersinia adhesin A, was used to assess the anti-adhesive potential of the modified PET. Contrarily to what was expected, adhesion of E. coli YadA was found to increase on the modified PET surfaces, exhibiting a clear preference for the crevices. This study highlights the role of material micro topography as an important attribute when considering bacterial adhesion.This work was supported by the ViBrANT project that received funding from the EU Horizon 2020 Research and Innovation Programme under the Marie Sklowdowska-Curie, Grant agreement no 765042 and the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UIDB/04469/2020.info:eu-repo/semantics/publishedVersio

Classification of control/pathologic subjects with support vector machines

The diagnosis of pathologies using vocal acoustic analysis has the advantage of been noninvasive and inexpensive technique compared to traditional technique in use. In this work the SVM were experimentally tested to diagnose dysphonia, chronic laryngitis or vocal cords paralysis. Three groups of parameters were experimented. Jitter, shimmer and HNR, MFCCs extracted from a sustained vowels and MFCC extracted from a short sentence. The first group showed their importance in this type of diagnose and the second group showed low discriminative power. The SVM functions and methods were also experimented using the dataset with and without gender separation. The best accuracy was 71% using the jitter, shimmer and HNR parameters without gender separation.info:eu-repo/semantics/publishedVersio

Long short term memory on chronic laryngitis classification

The classification study with the use of machine learning concepts has been applied for years, and one of the aspects in which this can be applied is for the analysis of speech acoustics applied to the analysis of pathologies. Among the pathologies present, one of them is chronic laryngitis. Thus, this article aims to present the results for a classification of chronic laryngitis with the use of Long Short Term Memory as a classifier. The parameters of relative jitter, relative shimmer and autocorrelation was used as input of the LSTM. A dataset of about 1500 instances were used to train, validate and test along 4 experiments with LSTM and one feedforward Artificial Neural Network (ANN). The results of the LSTM overcome the ones of the feedforward ANN, and was about 100% accuracy, sensitivity and specificity in test set, denoting a promising future for this classification tool in the voice pathologies diagnose.info:eu-repo/semantics/publishedVersio

Harmonic to noise ratio measurement - selection of window and length

Harmonic to Noise Ratio (HNR) measures the ratio between periodic and non-periodic components of a speech sound. It has become more and more important in the vocal acoustic analysis to diagnose pathologic voices. The measure of this parameter can be done with Praat software that is commonly accept by the scientific community has an accurate measure. Anyhow, this measure is dependent with the type of window used and its length. In this paper an analysis of the influence of the window and its length was made. The Hanning, Hamming and Blackman windows and the lengths between 6 and 24 glottal periods were experimented. Speech files of control subjects and pathologic subjects were used. The results showed that the Hanning window with the length of 12 glottal periods gives measures of HNR more close to the Praat measures.info:eu-repo/semantics/publishedVersio