Temporary destudentification caused by COVID-19: Motivations and effects on social relations in a Chilean university city.

The arrival of the coronavirus in 2020 brought major changes to education, with the rapid transition to online classes being the most significant. In the case of university students, the pandemic meant returning to their homes, which can be interpreted as a temporary destudentification. This manuscript analyses and interprets the motivations of university students from Temuco (Chile) to change their social relations and place of residence as a consequence of the COVID-19 pandemic. Through a quantitative methodology that used more than 800 online surveys and a principal component analysis, it was concluded that the psychological well-being and the security provided by the family were the main causes for changing accommodation; but a total of four main components related to material conditions, economic aspects, family and psychological and physical well-being were identified. Similarly, although with the pandemic the family was the most reinforced dimension in terms of social relations, there were groups of students who were more connected to friends and colleagues or neighbours. The results point to a partial and temporary destudentification, explainable by the nature of the lease contract and the dependent role of the students with respect to the landlords.

Classification of COVID-19 in X-ray images with Genetic Fine-tuning.

New and more transmissible SARS-COV-2 variants aggravated the SARS-COV-2 emergence. Lung X-ray images stand out as an alternative to support case screening. The latest computer-aided diagnosis systems have been using Deep Learning (DL) to detect pulmonary diseases. In this context, our work investigates different types of pneumonia detection, including COVID-19, based on X-ray image processing and DL techniques. Our methodology comprehends a pre-processing step including data-augmentation, contrast enhancement, and resizing method to overcome the challenge of heterogeneous and few samples of public datasets. Additionally, we propose a new Genetic Fine-Tuning method to automatically define an optimal set of hyper-parameters of ResNet50 and VGG16 architectures. Our results are encouraging; we achieve an accuracy of 97% considering three classes: COVID-19, other pneumonia, and healthy. Thus, our methodology could assist in classifying COVID-19 pneumonia, which could reduce costs by making the process faster and more efficient.

Detecting pulmonary diseases using deep features in X-ray images.

COVID-19 leads to radiological evidence of lower respiratory tract lesions, which support analysis to screen this disease using chest X-ray. In this scenario, deep learning techniques are applied to detect COVID-19 pneumonia in X-ray images, aiding a fast and precise diagnosis. Here, we investigate seven deep learning architectures associated with data augmentation and transfer learning techniques to detect different pneumonia types. We also propose an image resizing method with the maximum window function that preserves anatomical structures of the chest. The results are promising, reaching an accuracy of 99.8% considering COVID-19, normal, and viral and bacterial pneumonia classes. The differentiation between viral pneumonia and COVID-19 achieved an accuracy of 99.8%, and 99.9% of accuracy between COVID-19 and bacterial pneumonia. We also evaluated the impact of the proposed image resizing method on classification performance comparing with the bilinear interpolation; this pre-processing increased the classification rate regardless of the deep learning architectures used. We c ompared our results with ten related works in the state-of-the-art using eight sets of experiments, which showed that the proposed method outperformed them in most cases. Therefore, we demonstrate that deep learning models trained with pre-processed X-ray images could precisely assist the specialist in COVID-19 detection.

Parâmetros ruminais e balanço de nitrogênio em bovinos alimentados com silagem da raiz de mandioca / Ruminal parameters and nitrogen balance in fed cattle feeding with cassava root silage

Avaliou-se o efeito da inclusão da silagem da raiz de mandioca sobre os parâmetros ruminais e o balanço de compostos nitrogenados em bovinos de origem leiteira. Utilizou-se cinco animais, canulados no rúmen, não lactantes e com peso corporal médio de 389 kg. Os animais foram distribuídos em um quadrado latino cinco x cinco, sendo cinco dietas com níveis de inclusão (0,00; 3,62; 7,23; 10,84; e 14,54% da matéria seca da dieta) da silagem da raiz de mandioca e cinco períodos. Cada período constituiu-se em 10 dias de adaptação e cinco dias para a coleta dos dados. As excreções de nitrogênio na urina e nas fezes não foram influenciadas (P>0,05) pela inclusão da silagem da raiz de mandioca nas dietas. O consumo de nitrogênio total (CNT) e o balanço de nitrogênio (BN) apresentaram comportamento quadrático e linear crescente, respectivamente. Obteve-se o menor CNT (142,14 g/dia) no nível de inclusão de 5,82% de silagem da raiz de mandioca. As concentrações de ureia (U) e de nitrogênio ureico (NU) na urina e no plasma não modificaram (P>0,05). Observou-se comportamento quadrático (P<0,05) nas excreções de U e NU na urina, com ponto de mínimo de 131,13 e 61,20 g/dia, respectivamente, no nível de 7,27% de inclusão da silagem da raiz de mandioca. Não houve interação (P>0,05) entre os níveis da silagem da raiz de mandioca e o tempo de coleta do conteúdo ruminal para os ácidos graxos de cadeia curta, o pH e o nitrogênio amoniacal (N-NH3). Apenas o teor de N-NH3 apresentou comportamento quadrático, em função dos níveis de inclusão, obtendo-se o ponto mínimo (12,62 mg/100 mL de conteúdo ruminal) no nível de 5,98%. O nível de 7,23% de silagem da raiz de mandioca na dieta foi mais eficiente na utilização dos compostos nitrogenados. As dietas contribuem de forma semelhante para a produção dos ácidos graxos de cadeia curta, sem interferir no pH ruminal.(AU)

The effect of inclusion of cassava root silage on ruminal parameters and nitrogenous compounds in dairy cattle was evaluated. Five cattle cannulated in the rumen and with average body weight of 389 kg were distributed into a Latin square 5x5, with five levels of inclusion (0.00, 3.62, 7.23, 10.84 and 14.54% of the diet dry matter) of cassava root silage and five periods (10 days for adaptation and five days for data collection). The nitrogen excretion in urine and feces were not affected (P>0.05) by inclusion of cassava root silage in the diet. The total nitrogen intake (CNT) and nitrogen balance (NB) showed an increasing quadratic and linear behavior, respectively. The lowest CNT (142.14g/day) was obtained with the inclusion of 5.82% silage cassava root. The concentration of urea (U) and urea nitrogen (UN) in plasma and urine did not change (P>0.05). There was a quadratic behavior (P<0.05) in excreta of U and NU in the urine, with minimum point of 131.13 and 61.20g/day respectively, at the level of 7.27% inclusion of the cassava root silage. No interaction (P>0.05) was between the levels of cassava root silage and the collection time of rumen contents for the short-chain fatty acids, pH and ammonia nitrogen (NH3-N). Only the N-NH3 protein showed quadratic behavior, according to the inclusion levels, with the minimum point (12.62mg/100ml of rumen contents) at the level of 5.98%. The level of 7.23% of cassava root silage in the diet was more efficient with the use of nitrogen compounds. The diets contribute similarly to the production of short chain fatty acids, without disturbing the rumen pH.(AU)

Molecular dynamics investigation of a density-driven glass transition in a liquid crystal system.

Molecular dynamics simulations are carried out to address the density-driven glass transition in a system of rodlike particles that interact with the Gay-Berne potential. Since crystallization occurs in this system on the time scale of the simulations, direct simulation of the glass transition is not possible. Instead, glasses with isotropic orientational order are heated to a temperature T, and the relaxation times by which nematic orientational order develops are determined. These relaxation times appear to diverge at a critical density rho(c); i.e., the system can equilibrate at rhorho(c) (at the temperature T). The relaxation times follow a power-law scaling as the critical density is approached, suggesting that this density-driven glass transition concurs with mode coupling theory.