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70 Research products, page 1 of 7

  • COVID-19
  • Other research products
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  • COVID-19

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  • Other research product . Other ORP type . 2022
    Closed Access Slovenian
    Authors: 
    Melinc Mlekuž, Maja;
    Country: Slovenia

    Prispevek predstavlja izhodišča za razpravo o jezikovnih smernicah in učnih ciljih v vrtcih in šolah s slovenskim učnim jezikom v Tržaški in Goriški pokrajini ter v večstopenjski šoli s slovensko-italijanskim dvojezičnim poukom v Špetru. Izhaja iz rezultatov kvantitativne raziskave o poteku pouka na daljavo med epidemijo covid-19, izvedene med pedagoškim kadrom, dijaki in starši otrok, ki obiskujejo vrtce in šole s slovenskim učnim jezikom in dvojezičnim slovensko-italijanskim poukom v Italiji. Izsledke dopolnjuje analiza petnajstih polstrukturiranih globinskih intevjujev z učitelji o didaktično-metodičnih izzivih pri poučevanju učencev, katerih prvi ali primarni jezik ni slovenski, slovenščina pa tudi ni jezik okolja, v katerem živijo.

  • Open Access English
    Authors: 
    Bergant, Martina; de Marco, Ario;
    Country: Slovenia
  • Open Access Slovenian
    Authors: 
    Damjan, Matija;
    Publisher: Univerza v Mariboru, Univerzitetna založba
    Country: Slovenia

    Sporazum TRIPS je bil pomembno gonilo standardizacije pravne zaščite farmacevtskih izdelkov s pravicami intelektualne lastnine na svetovni ravni. Za primere izrednih razmer, ko mora javni interes prevladati nad zasebnimi pravicami, predvideva uporabo prisilne licence, ki se podeli za vsako državo posebej. Pandemija covida-19 je po celem svetu hkrati povzročila potrebo po pospešitvi proizvodnje in distribucije patentiranih cepiv, zdravil in medicinske opreme. V okviru STO se zato obravnava predlog, da bi v svetovni zdravstveni krizi vse države začasno oprostili obveznosti spoštovanja pravic intelektualne lastnine iz Sporazuma TRIPS in tako z enkratnim ukrepom odpravili pravne ovire za pravičen dostop do cepiv in zdravil po svetu. Prispevek predstavlja ukrepe za varstvo javnega zdravja v skladu s Sporazumom TRIPS in njihove pomanjkljivosti ter analizira, kako bi v domačem pravu učinkovala predlagana oprostitev obveznosti varovanja pravic intelektualne lastnine. TRIPS Agreement has been an important driver of the global standardisation of legal protection of pharmaceuticals with intellectual property rights. For the cases of emergency, where the public interest must prevail over private rights, the Agreement provides for the use of compulsory licensing granted on a country-by-country basis. The Covid-19 pandemic created the need to accelerate the production and distribution of patented vaccines, medicines, and medical equipment simultaneously all around the world. The WTO is therefore considering a proposal to temporarily exempt all member states from the obligation to respect intellectual property rights under the TRIPS Agreement in the wake of the global health crisis in order to remove legal barriers to fair access to vaccines and medicines worldwide. The paper presents measures for the protection of public health under the TRIPS Agreement, as well as their shortcomings, and analyses how the proposed waiver of intellectual property rights would operate in domestic law.

  • Open Access English
    Authors: 
    Kobal Grum, Darja; Babnik, Katarina;
    Publisher: Frontiers Research Foundation
    Country: Slovenia

    Unlike environmental sustainability, social sustainability in the workplace is a relatively new concept that is still searching for its own definition and explanation. Therefore, in this paper, we systematically reviewed and critically evaluated recent research on this topic. In doing so, we identified important constructs that help us better define and understand the phenomenon of social sustainability in the workplace. We focused on articles from 2016 to 2022 with content related to three Sustainable Development Goals (SDGs), namely health and wellbeing (SDG-3), gender equality (SDG-5), and decent work (SDG-8). Given the harrowing events of the past 2 years, triggered by the COVID-19 pandemic and the global impact of the war in Ukraine, we also wanted to learn whether other categories, such as security (SDG-11) and peace (SDG-16), are embedded in the concept of social sustainability at work. The articles we studied were found through EBSCOhost, specifically in the Academic Search Complete, Business Source Premier, APA PsycInfo, SocINDEX with Full Text, and GreenFILE databases. We selected 67 articles and organized them according to the four levels of research and practice in work and organizational psychology. In reviewing the literature, we identified several constructs that can be classified at four levels of interest in work and organizational psychology. At the level focused on the job/work, we identified two main topics: (i) sustainable job/work characteristics and (ii) sustainable job (re)design. At the people-focused level, we identified the following topics: (i) pro-sustainable self-system, (ii) pro-sustainable job attitudes and motivation, (iii) sustainability work environment perceptions and other mediating mechanisms, and (iv) sustainable job behavior. The organization-focused level includes (i) organizations as human systems and (ii) pro-sustainable organizational policies and practices. The last (society- focused) level is defined by two main topics: (i) understanding society as a human system and (ii) pro-social mechanisms. In the discussion, we categorized specific constructs identified within the described focus levels into the theoretical model describing the psychological concept of social sustainability in the workplace from the perspective of sustainable goals.

  • Other research product . Other ORP type . 2022
    Open Access English
    Authors: 
    Lavtižar, Vesna; Oarga-Mulec, Andreea;
    Country: Slovenia
  • Closed Access English
    Authors: 
    Mohanachandran Nair Sindhu, Swapna;
    Country: Slovenia

    Cough signal analysis for understanding the pathological condition has become important from the outset of the exigency posed by the epidemic COVID-19. The present work suggests a surrogate approach for the classification of cough signals - croup cough (CC) and pertussis (PT) – based on spectral, fractal, and nonlinear time-series techniques. The spectral analysis of CC reveals the presence of more frequency components in the short duration cough sound compared to PT. The musical nature of CC is unveiled not only through the spectral analysis but also through the phase portrait features – sample entropy (S), maximal Lyapunov exponent (L), and Hurst exponent (Hb). The modifications in the internal morphology of the respiratory tract, giving rise to more frequency components associated with the complex airflow dynamics, get staged through the higher fractal dimension of CC. Among the two supervised classification tools, cubic KNN (CKNN) and neural net pattern recognition (NNPR), used for classifying the CC and PT signals based on nonlinear time series parameters, NNPR is found better. Thus, the study opens the possibility of identification of pulmonary pathological conditions through cough sound signal analysis.

  • Other research product . Other ORP type . 2022
    Closed Access English
    Authors: 
    Mohanachandran Nair Sindhu, Swapna; VIMAL, RAJ; S, Sankararaman;
    Country: Slovenia

    The paper proposes a graph-theoretical approach to auscultation, bringing out the potential of graph features in classifying the bioacoustics signals. The complex network analysis of the bioacoustics signals - vesicular (VE) and bronchial (BR) breath sound - of 48 healthy persons are carried out for understanding the airflow dynamics during respiration. The VE and BR are classified by the machine learning techniques extracting the graph features – the number of edges (E), graph density (D), transitivity (T), degree centrality (Dcg) and eigenvector centrality (Ecg). The higher value of E, D, and T in BR indicates the temporally correlated airflow through the wider tracheobronchial tract resulting in sustained high-intense low-frequencies. The frequency spread and high-frequencies in VE, arising due to the less correlated airflow through the narrow segmental bronchi and lobar, appears as a lower value for E, D, and T. The lower values of Dcg and Ecg justify the inferences from the spectral and other graph parameters. The study proposes a methodology in remote auscultation that can be employed in the current scenario of COVID-19.

  • Other research product . Other ORP type . 2022
    Closed Access English
    Authors: 
    Swapna, Mohanachandran Nair Sindhu; Sreejyothi, S.; Raj, Vimal; Sankararaman, Sankaranarayana Iyer;
    Country: Slovenia

    A first report of unveiling the fractality and fractal nature of severe acute respiratory syndrome coronavirus (SARS CoV-2) responsible for the pandemic disease widely known as coronavirus disease 2019 (COVID 19) is presented. The fractal analysis of the electron microscopic and atomic force microscopic images of 40 coronaviruses (CoV), by the normal and differential box-counting method, reveals its fractal structure. The generalised dimension indicates the multifractal nature of the CoV. The higher value of fractal dimension and lower value of Hurst exponent (H) suggest higher complexity and greater roughness. The statistical analysis of generalised dimension and H is understood through the notched box plot. The study on CoV clusters also confirms its fractal nature. The scale-invariant value of the box-counting fractal dimension of CoV yields a value of 1.820. The study opens the possibility of exploring the potential of fractal analysis in the medical diagnosis of SARS CoV-2.

  • Closed Access English
    Authors: 
    MOHANACHANDRAN NAIR SINDHU, SWAPNA;
    Country: Slovenia

    The paper proposes a novel approach to bring out the potential of complex networks based on graph theory to unwrap the hidden characteristics of cough signals, croup (BC), and pertussis (PS). The spectral and complex network analyses of 48 cough sounds are utilized for understanding the airflow through the infected respiratory tract. Among the different phases of the cough sound time-domain signals of BC and PS – expulsive (X), intermediate (I), and voiced (V) - the phase ‘I’ is noisy in BC due to improper glottal functioning. The spectral analyses reveal high-frequency components in both cough signals with an additional high-intense low-frequency spread in BC. The complex network features created by the correlation mapping approach, like number of edges (E), graph density (G), transitivity (), degree centrality (D), average path length (L), and number of components () distinguishes BC and PS. The higher values of E, G, and for BC indicate its musical nature through the strong correlation between the signal segments and the presence of high-intense low-frequency components in BC, unlike that in PS. The values of D, L, and discriminate BC and PS in terms of the strength of the correlation between the nodes within them. The linear discriminant analysis (LDA) and quadratic support vector machine (QSVM) classifies BC and PS, with greater accuracy of 94.11% for LDA. The proposed work opens up the potentiality of employing complex networks for cough sound analysis, which is vital in the current scenario of COVID-19.

  • Closed Access English
    Authors: 
    MOHANACHANDRAN NAIR SINDHU, SWAPNA;
    Country: Slovenia

    This article proposes a unique approach to bring out the potential of graph-based features to reveal the hidden signatures of wet (WE) and dry (DE) cough signals, which are the suggestive symptoms of various respiratory ailments like COVID 19. The spectral and complex network analyses of 115 cough signals are employed for perceiving the airflow dynamics through the infected respiratory tract while coughing. The different phases of WE and DE are observed from their time-domain signals, indicating the operation of the glottis. The wavelet analysis of WE shows a frequency spread due to the turbulence in the respiratory tract. The complex network features namely degree centrality, eigenvector centrality, transitivity, graph density and graph entropy not only distinguish WE and DE but also reveal the associated airflow dynamics. A better distinguishability between WE and DE is obtained through the supervised machine learning techniques (MLTs)—quadratic support vector machine and neural net pattern recognition (NN), when compared to the unsupervised MLT, principal component analysis. The 93.90% classification accuracy with a precision of 97.00% suggests NN as a better classifier using complex network features. The study opens up the possibility of complex network analysis in remote auscultation.

Advanced search in Research products
Research products
arrow_drop_down
Searching FieldsTerms
Any field
arrow_drop_down
includes
arrow_drop_down
Include:
The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
70 Research products, page 1 of 7
  • Other research product . Other ORP type . 2022
    Closed Access Slovenian
    Authors: 
    Melinc Mlekuž, Maja;
    Country: Slovenia

    Prispevek predstavlja izhodišča za razpravo o jezikovnih smernicah in učnih ciljih v vrtcih in šolah s slovenskim učnim jezikom v Tržaški in Goriški pokrajini ter v večstopenjski šoli s slovensko-italijanskim dvojezičnim poukom v Špetru. Izhaja iz rezultatov kvantitativne raziskave o poteku pouka na daljavo med epidemijo covid-19, izvedene med pedagoškim kadrom, dijaki in starši otrok, ki obiskujejo vrtce in šole s slovenskim učnim jezikom in dvojezičnim slovensko-italijanskim poukom v Italiji. Izsledke dopolnjuje analiza petnajstih polstrukturiranih globinskih intevjujev z učitelji o didaktično-metodičnih izzivih pri poučevanju učencev, katerih prvi ali primarni jezik ni slovenski, slovenščina pa tudi ni jezik okolja, v katerem živijo.

  • Open Access English
    Authors: 
    Bergant, Martina; de Marco, Ario;
    Country: Slovenia
  • Open Access Slovenian
    Authors: 
    Damjan, Matija;
    Publisher: Univerza v Mariboru, Univerzitetna založba
    Country: Slovenia

    Sporazum TRIPS je bil pomembno gonilo standardizacije pravne zaščite farmacevtskih izdelkov s pravicami intelektualne lastnine na svetovni ravni. Za primere izrednih razmer, ko mora javni interes prevladati nad zasebnimi pravicami, predvideva uporabo prisilne licence, ki se podeli za vsako državo posebej. Pandemija covida-19 je po celem svetu hkrati povzročila potrebo po pospešitvi proizvodnje in distribucije patentiranih cepiv, zdravil in medicinske opreme. V okviru STO se zato obravnava predlog, da bi v svetovni zdravstveni krizi vse države začasno oprostili obveznosti spoštovanja pravic intelektualne lastnine iz Sporazuma TRIPS in tako z enkratnim ukrepom odpravili pravne ovire za pravičen dostop do cepiv in zdravil po svetu. Prispevek predstavlja ukrepe za varstvo javnega zdravja v skladu s Sporazumom TRIPS in njihove pomanjkljivosti ter analizira, kako bi v domačem pravu učinkovala predlagana oprostitev obveznosti varovanja pravic intelektualne lastnine. TRIPS Agreement has been an important driver of the global standardisation of legal protection of pharmaceuticals with intellectual property rights. For the cases of emergency, where the public interest must prevail over private rights, the Agreement provides for the use of compulsory licensing granted on a country-by-country basis. The Covid-19 pandemic created the need to accelerate the production and distribution of patented vaccines, medicines, and medical equipment simultaneously all around the world. The WTO is therefore considering a proposal to temporarily exempt all member states from the obligation to respect intellectual property rights under the TRIPS Agreement in the wake of the global health crisis in order to remove legal barriers to fair access to vaccines and medicines worldwide. The paper presents measures for the protection of public health under the TRIPS Agreement, as well as their shortcomings, and analyses how the proposed waiver of intellectual property rights would operate in domestic law.

  • Open Access English
    Authors: 
    Kobal Grum, Darja; Babnik, Katarina;
    Publisher: Frontiers Research Foundation
    Country: Slovenia

    Unlike environmental sustainability, social sustainability in the workplace is a relatively new concept that is still searching for its own definition and explanation. Therefore, in this paper, we systematically reviewed and critically evaluated recent research on this topic. In doing so, we identified important constructs that help us better define and understand the phenomenon of social sustainability in the workplace. We focused on articles from 2016 to 2022 with content related to three Sustainable Development Goals (SDGs), namely health and wellbeing (SDG-3), gender equality (SDG-5), and decent work (SDG-8). Given the harrowing events of the past 2 years, triggered by the COVID-19 pandemic and the global impact of the war in Ukraine, we also wanted to learn whether other categories, such as security (SDG-11) and peace (SDG-16), are embedded in the concept of social sustainability at work. The articles we studied were found through EBSCOhost, specifically in the Academic Search Complete, Business Source Premier, APA PsycInfo, SocINDEX with Full Text, and GreenFILE databases. We selected 67 articles and organized them according to the four levels of research and practice in work and organizational psychology. In reviewing the literature, we identified several constructs that can be classified at four levels of interest in work and organizational psychology. At the level focused on the job/work, we identified two main topics: (i) sustainable job/work characteristics and (ii) sustainable job (re)design. At the people-focused level, we identified the following topics: (i) pro-sustainable self-system, (ii) pro-sustainable job attitudes and motivation, (iii) sustainability work environment perceptions and other mediating mechanisms, and (iv) sustainable job behavior. The organization-focused level includes (i) organizations as human systems and (ii) pro-sustainable organizational policies and practices. The last (society- focused) level is defined by two main topics: (i) understanding society as a human system and (ii) pro-social mechanisms. In the discussion, we categorized specific constructs identified within the described focus levels into the theoretical model describing the psychological concept of social sustainability in the workplace from the perspective of sustainable goals.

  • Other research product . Other ORP type . 2022
    Open Access English
    Authors: 
    Lavtižar, Vesna; Oarga-Mulec, Andreea;
    Country: Slovenia
  • Closed Access English
    Authors: 
    Mohanachandran Nair Sindhu, Swapna;
    Country: Slovenia

    Cough signal analysis for understanding the pathological condition has become important from the outset of the exigency posed by the epidemic COVID-19. The present work suggests a surrogate approach for the classification of cough signals - croup cough (CC) and pertussis (PT) – based on spectral, fractal, and nonlinear time-series techniques. The spectral analysis of CC reveals the presence of more frequency components in the short duration cough sound compared to PT. The musical nature of CC is unveiled not only through the spectral analysis but also through the phase portrait features – sample entropy (S), maximal Lyapunov exponent (L), and Hurst exponent (Hb). The modifications in the internal morphology of the respiratory tract, giving rise to more frequency components associated with the complex airflow dynamics, get staged through the higher fractal dimension of CC. Among the two supervised classification tools, cubic KNN (CKNN) and neural net pattern recognition (NNPR), used for classifying the CC and PT signals based on nonlinear time series parameters, NNPR is found better. Thus, the study opens the possibility of identification of pulmonary pathological conditions through cough sound signal analysis.

  • Other research product . Other ORP type . 2022
    Closed Access English
    Authors: 
    Mohanachandran Nair Sindhu, Swapna; VIMAL, RAJ; S, Sankararaman;
    Country: Slovenia

    The paper proposes a graph-theoretical approach to auscultation, bringing out the potential of graph features in classifying the bioacoustics signals. The complex network analysis of the bioacoustics signals - vesicular (VE) and bronchial (BR) breath sound - of 48 healthy persons are carried out for understanding the airflow dynamics during respiration. The VE and BR are classified by the machine learning techniques extracting the graph features – the number of edges (E), graph density (D), transitivity (T), degree centrality (Dcg) and eigenvector centrality (Ecg). The higher value of E, D, and T in BR indicates the temporally correlated airflow through the wider tracheobronchial tract resulting in sustained high-intense low-frequencies. The frequency spread and high-frequencies in VE, arising due to the less correlated airflow through the narrow segmental bronchi and lobar, appears as a lower value for E, D, and T. The lower values of Dcg and Ecg justify the inferences from the spectral and other graph parameters. The study proposes a methodology in remote auscultation that can be employed in the current scenario of COVID-19.

  • Other research product . Other ORP type . 2022
    Closed Access English
    Authors: 
    Swapna, Mohanachandran Nair Sindhu; Sreejyothi, S.; Raj, Vimal; Sankararaman, Sankaranarayana Iyer;
    Country: Slovenia

    A first report of unveiling the fractality and fractal nature of severe acute respiratory syndrome coronavirus (SARS CoV-2) responsible for the pandemic disease widely known as coronavirus disease 2019 (COVID 19) is presented. The fractal analysis of the electron microscopic and atomic force microscopic images of 40 coronaviruses (CoV), by the normal and differential box-counting method, reveals its fractal structure. The generalised dimension indicates the multifractal nature of the CoV. The higher value of fractal dimension and lower value of Hurst exponent (H) suggest higher complexity and greater roughness. The statistical analysis of generalised dimension and H is understood through the notched box plot. The study on CoV clusters also confirms its fractal nature. The scale-invariant value of the box-counting fractal dimension of CoV yields a value of 1.820. The study opens the possibility of exploring the potential of fractal analysis in the medical diagnosis of SARS CoV-2.

  • Closed Access English
    Authors: 
    MOHANACHANDRAN NAIR SINDHU, SWAPNA;
    Country: Slovenia

    The paper proposes a novel approach to bring out the potential of complex networks based on graph theory to unwrap the hidden characteristics of cough signals, croup (BC), and pertussis (PS). The spectral and complex network analyses of 48 cough sounds are utilized for understanding the airflow through the infected respiratory tract. Among the different phases of the cough sound time-domain signals of BC and PS – expulsive (X), intermediate (I), and voiced (V) - the phase ‘I’ is noisy in BC due to improper glottal functioning. The spectral analyses reveal high-frequency components in both cough signals with an additional high-intense low-frequency spread in BC. The complex network features created by the correlation mapping approach, like number of edges (E), graph density (G), transitivity (), degree centrality (D), average path length (L), and number of components () distinguishes BC and PS. The higher values of E, G, and for BC indicate its musical nature through the strong correlation between the signal segments and the presence of high-intense low-frequency components in BC, unlike that in PS. The values of D, L, and discriminate BC and PS in terms of the strength of the correlation between the nodes within them. The linear discriminant analysis (LDA) and quadratic support vector machine (QSVM) classifies BC and PS, with greater accuracy of 94.11% for LDA. The proposed work opens up the potentiality of employing complex networks for cough sound analysis, which is vital in the current scenario of COVID-19.

  • Closed Access English
    Authors: 
    MOHANACHANDRAN NAIR SINDHU, SWAPNA;
    Country: Slovenia

    This article proposes a unique approach to bring out the potential of graph-based features to reveal the hidden signatures of wet (WE) and dry (DE) cough signals, which are the suggestive symptoms of various respiratory ailments like COVID 19. The spectral and complex network analyses of 115 cough signals are employed for perceiving the airflow dynamics through the infected respiratory tract while coughing. The different phases of WE and DE are observed from their time-domain signals, indicating the operation of the glottis. The wavelet analysis of WE shows a frequency spread due to the turbulence in the respiratory tract. The complex network features namely degree centrality, eigenvector centrality, transitivity, graph density and graph entropy not only distinguish WE and DE but also reveal the associated airflow dynamics. A better distinguishability between WE and DE is obtained through the supervised machine learning techniques (MLTs)—quadratic support vector machine and neural net pattern recognition (NN), when compared to the unsupervised MLT, principal component analysis. The 93.90% classification accuracy with a precision of 97.00% suggests NN as a better classifier using complex network features. The study opens up the possibility of complex network analysis in remote auscultation.