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This article explores how state and society relations have been affected by the development of information technology in China over the past 20 years. It argues that despite all the transformative changes that such technology has helped bring about, ?benefits? have to be weighed in terms of both empowerment of society and strengthening of state capacity. Ultimately, the digital challenge has not translated into a weakening of the authoritarian state, and this can be explained by the very nature of the party-state in China and how it has managed to make use of communication tools that prove to be both constructive and divisive.

The protein adsorption capacity of different materials was evaluated to assess their potential efficacy as alternative adsorbents for the removal of proteins from wines, with the purpose of finding suitable low-swelling materials that could be used in a percolated bed. The adsorbents tested were thermally treated sodium bentonite, low-swelling adsorbing clays, ion exchange resins and other protein adsorbents (silica gel, hydroxyapatite and alumina). The materials were evaluated by analysing both the capacity to stabilize untreated white wines, according to a heat test, and by characterizing the adsorption isotherms of bovine serum albumin (BSA) in a model wine (water, ethanol and K-bitartrate). Breakthrough curves in a packed bed were determined experimentally for some materials, showing the influence of the adsorption isotherm shape. Some ion-exchange resins showed a favourable behaviour and have good potential as alternative adsorbents.

Integrating information literacy into learning improves student performance and, for that reason, academic librarians can play a significant role by collaborating in the design and training programs in these areas. In Macao, there is no known study on the information literacy performance of higher education students, so we seek to diagnose this area. For that purpose, a survey was applied to higher education students to assess students' perception of information literacy and their self-characterization regarding the use of resources and the type of skills needed for academic work. A semi-structured interview was also carried out with teachers about the same reality. Students perceive themselves to have a low level of confidence in the performance of their academic tasks, which affects their fulfilment. Faculty are aligned with this diagnosis, revealing the students’ weaknesses in the information search and presentation. Overall, information needs are evident among students as also is the use of preferred information resources in pursuit of their studies. The training aimed at students in search, retrieval, analysis, and use of information seems to be essential, which is why the construction of a tailormade training program in Information Literacy is anticipated.

La crisi del Covid-19 ha evidenziato il disagio e il divario sempre più ampio tra ricchi e poveri. La crisi finanziaria del 2007-2009 era già risuonata come un campa­nello d'allarme sulla necessità di

In the paper carried out by Wenjun et al. [Phys. Rev. A 95, 032124 (2017)], a generalization of the James effective dynamics theory based on a first version of the James method was presented. However, we contend that this is not a very rigorous way of deriving the effective third-order expansion for an interaction Hamiltonian with harmonic time-dependence. In fact, here we show that the third-order Hamiltonian obtained by Wenjun et al. is not Hermitian for general situations when we consider time dependence. Its non-Hermitian nature arises from the foundation of the theory itself. In this comment paper, the most general expression of the effective Hamiltonian expanded up to third order is obtained. Our derived effective Hamiltonian is Hermitian even in situations where we have time dependence.

In recent years, the integration of Machine Learning (ML) techniques in the field of healthcare and public health has emerged as a powerful tool for improving decision-making processes [...]

Este trabalho consiste numa análise multimodal das estratégias discursivas de Bernie Sanders e Hillary Clinton num excerto de um debate sobre as benesses dadas pela senadora norte americana aos bancos no pós-crise económica global de 2008. Bernie Sanders e Hillary Clinton evidenciaram uma linguagem corporal diferente, tanto na posição de locutor como na de interlocutor. No entanto, mesmo utilizando estratégias de comunicação verbal e física diferentes, os gestos utilizados enquadram-se no campo dos gestos recorrentemente observados em figuras políticas em estudos feitos por outros autores. Reforça-se assim a ideia de que os gestos em questão são regularmente utilizados por figuras políticas.

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Since the beginning of 2020, Coronavirus Disease 19 (COVID-19) has attracted the attention of the World Health Organization (WHO). This paper looks into the infection mechanism, patient symptoms, and laboratory diagnosis, followed by an extensive assessment of different technologies and computerized models (based on Electrocardiographic signals (ECG), Voice, and X-ray techniques) proposed as a diagnostic tool for the accurate detection of COVID-19. The found papers showed high accuracy rate results, ranging between 85.70% and 100%, and F1-Scores from 89.52% to 100%. With this state-of-the-art, we concluded that the models proposed for the detection of COVID-19 already have significant results, but the area still has room for improvement, given the vast symptomatology and the better comprehension of individuals’ evolution of the disease.

Objective: This study highlights the potential of an Electrocardiogram (ECG) as a powerful tool for early diagnosis of COVID-19 in critically ill patients with limited access to CT–Scan rooms. Methods: In this investigation, 3 categories of patient status were considered: Low, Moderate, and Severe. For each patient, 2 different body positions have been used to collect 2 ECG signals. Then, from each collected signal, 10 non-linear features (Energy, Approximate Entropy, Logarithmic Entropy, Shannon Entropy, Hurst Exponent, Lyapunov Exponent, Higuchi Fractal Dimension, Katz Fractal Dimension, Correlation Dimension and Detrended Fluctuation Analysis) were extracted every 1s ECG time-series length to serve as entries for 19 Machine learning classifiers within a leave-one-out cross-validation procedure. Four different classification scenarios were tested: Low vs. Moderate, Low vs. Severe, Moderate vs. Severe and one Multi-class comparison (All vs. All). Results: The classification report results were: (1) Low vs. Moderate - 100% of Accuracy and 100% of F1–Score; (2) Low vs. Severe - Accuracy of 91.67% and an F1–Score of 94.92%; (3) Moderate vs. Severe - Accuracy of 94.12% and an F1–Score of 96.43%; and (4) All vs All - 78.57% of Accuracy and 84.75% of F1–Score. Conclusion: The results indicate that the applied methodology could be considered a good tool for distinguishing COVID-19’s different severity stages using ECG signals. Significance: The findings highlight the potential of ECG as a fast and effective tool for COVID-19 examination. In comparison to previous studies using the same database, this study shows a 7.57% improvement in diagnostic accuracy for the All vs All comparison.

Introduction: SARS-CoV-2, a virus responsible for the emergence of the life-threatening disease known as COVID-19, exhibits a diverse range of clinical manifestations. The spectrum of symptoms varies widely, encompassing mild to severe presentations, while a considerable portion of the population remains asymptomatic. COVID-19, primarily a respiratory virus, has been linked to cardiovascular complications in some patients. Notably, cardiac issues can also arise after recovery, contributing to post-acute COVID-19 syndrome, a significant concern for patient health. The present study intends to evaluate the post-acute COVID-19 syndrome cardiovascular effect through ECG by comparing patients affected with cardiac diseases without COVID-19 diagnosis report (class 1) and patients with cardiac pathologies who present post-acute COVID-19 syndrome (class 2). Methods: From 2 body positions, a total of 10 non-linear features, extracted every 1 second under a multi-band analysis performed by Discrete Wavelet Transform (DWT), have been compressed by 6 statistical metrics to serve as inputs for an individual feature analysis by the means of Mann-Whitney U-test and XROC classification. Results and Discussion: 480 Mann-Whitney U-test statistical analyses and XROC discrimination approaches have been done. The percentage of statistical analysis with significant differences (p<0.05) was 30.42% (146 out of 480). The best overall results were obtained by approximating the feature Energy, with the data compressor Kurtosis in the body position Down. Those results were 83.33% of Accuracy, 83.33% of Sensitivity, 83.33% of Specificity and 87.50% of AUC. Conclusions: The results show that the applied methodology can be a way to show changes in cardiac behaviour provoked by post-acute COVID-19 syndrome.

In the past decades, the field of cinema has undergone several transformations. The digital turn increasingly called for new forms of production, distribution, and exhibition, which imply different ways of thinking, doing, and experimenting cinema. These new forms also reduced the gap between cinema to other so-called visual arts. If cinema and visual arts were already in the process of merging, the last years forced the naturalization of thinking in similar theoretical grounds. This special issue aims to be a forum for the discussion of new practices of researching cinema, and the changes in cinema’s forms of experience and production.