ABSTRACT
The COVID-19 pandemics required the countries to take decisions rapidly. Consequently, the National Institute of Health (INS) developed a series of documents of scientific evidence synthesis according to the Ministry of Health's requirements. Based on these reports, the INS developed recommendations to update normative documents related to COVID-19's management. This article describes the construction of a new methodology applied by the INS to synthesize scientific evidence during the COVID-19 pandemic. Moreover, it emphasizes the efforts and strategies used to guarantee the methodological quality and the implementation of the GRADE approach. Finally, it provides a short reflection on the limitations and challenges of using evidence to design national public policies in the future. © 2022 Publicado por Cuerpo Médico Hospital Nacional Almanzor Aguinaga Asenjo.
ABSTRACT
COVID-19 has aspects on its pathogenesis that still need elucidating and an analysis of clinical and immunogenetic factors in each cohort of patients is paramount to understanding how genetic variability can explain the multiple clinical spectra seen in patients infected with SARS-CoV-2. The aim of this study was to correlate the KIR polymorphism/HLA class I ligand interactions from patients and healthy subjects with either the susceptibility or severity to COVID-19. Genotyping of HLA-A, -B, -C and KIR genes were carried out from 459 symptomatic as well as 667 non-infected Spanish Caucasian individuals using Lifecodes HLA-SSO and KIR-SSO kits (ImmucorTM, USA) and analyzed in the Luminex in this uni-centre case-control study performed at the University Hospital of Salamanca, Spain. Comparative KIR gene analysis showed that KIR2DS4 was significantly more representative in healthy versus infected individuals. When comparing subgroups of infected patients, KIR2DS3 had a higher frequency in those who progressed to a more severity disease and yet with higher mortality rate. Three functional combinations were significant on univariate analysis: KIR2DL2/C1, KIR2DS2/C1, and KIR2DS3/C1. However, in the multivariate analysis, only the KIR2DL2/C1 interaction remained significant (OR = 15.2 (95% CI 1.5-147), p = 0.0189). Compared with the solo-clinical characteristics predictive model, that included well-known comorbidity variables such as hypertension, age, sex, diabetes, C-reactive protein, dyslipidemia, smoking, ferritin, and fibrinogen, the clinical-and-KIR-based model showed a better ability to discriminate between severe and nonsevere patients with higher sensitivity and specificity. Our results support a fundamental role of KIR/ligand interaction in the clinical course of COVID-19. Since the KIR2DL2 gene has a high frequency in Spain (60%), the analysis of the KIR2DL2/C1 in symptomatic patients who require hospitalization could be helpful to better determine their prognosis.
ABSTRACT
Deep Learning has been used for several applications including the analysis of medical images. Some transfer learning works show that an improvement in performance is obtained if a pre-trained model on ImageNet is transferred to a new task. Taking into account this, we propose a method that uses a pre-trained model on ImageNet to fine-tune it for Covid-19 detection. After the fine-tuning process, the units that produce a variance equal to zero are removed from the model. Finally, we test the features of the penultimate layer in different classifiers removing those that are less important according to the f-test. The results produce models with fewer units than the transferred model. Also, we study the attention of the neural network for classification. Noise and metadata printed in medical images can bias the performance of the neural network and it obtains poor performance when the model is tested on new data. We study the bias of medical images when raw and masked images are used for training deep models using a transfer learning strategy. Additionally, we test the performance on novel data in both models: raw and masked data. Author
ABSTRACT
In this work, forms of asynchronous interaction developed by university students during the Covid-19 pandemic are identified. Through a case study, the structure of participation and the discursive mechanisms used by four groups of students were analyzed;the groups discussed different educational topics over six weeks. Due to the process of adaptation to the virtual training modality, the groups presented various difficulties in maintaining constant and productive conversations in the forums;however, a slight improvement can be seen after the third week of work when the students begin to internalize the new modality. © GKAEdiciones, authors.
ABSTRACT
Traditionally, food sustainability has been considered solely in the stage of agricultural production. However, globalization, the expansion of the food production industry, and the emergence of supermarket chains that control the retail food market require specific significant changes in supply chains in the food sector and, therefore, we need to address the economic, social, and environmental impacts of these events. On the other hand, social selling has increased rapidly in recent years, with a further boom, following current events related to the coronavirus disease (COVID-19). This explosion of social sales, where there are usually no control and regulation entities, can bring problems associated with mishandling items. In this paper, we expose how Blockchain technology supports the traceability of social sales by validating the data provided by the chain participants such as digital health passports, production and transport data in the sale process;the proposed solution generates recommendations on productmanagement considering the agreements previously made by the network actors. To evaluate the proposed smart contracts, we useHyperledger Caliper, obtaining an average throughput of 12.6 transactions per second and an average latency of 0.3 s for the asset update process. We also use a study case to evaluate the proposed project platform's selling-transport stage using Internet of Things (IoT) sensors. © 2023 Tech Science Press. All rights reserved.
ABSTRACT
In recent years, the production and consumption of fossil jet fuel have increased as a consequence of a rise in the number of passengers and goods transported by air. Despite the low demand caused by the coronavirus 2019 pandemic, an increase in the services offered by the sector is expected again. In an economic context still dependent on scarce oil, this represents a problem. There is also a problem arising from the fuel's environmental impact throughout its life cycle. Given this, a promising solution is the use of biojet fuel as renewable aviation fuel. In a circular economy framework, the use of lignocellulosic biomass in the form of sugar-rich crop residues allows the production of alcohols necessary to obtain biojet fuel. The tools provided by process intensification also make it possible to design a sustainable process with low environmental impact and capable of achieving energy savings. The goal of this work was to design an intensified process to produce biojet fuel from Mexican lignocellulosic biomass, with alcohols as intermediates. The process was modeled following a sequence of pretreatment/hydrolysis/fermentation/purification for the biomass-ethanol process, and dehydration/oligomerization/hydrogenation/distillation for ethanol-biojet process under the concept of distributed configuration. To obtain a cleaner, greener, and cheaper process, the purification zone of ethanol was intensified by employing a vapor side stream distillation column and a dividing wall column. Once designed, the entire process was optimized by employing the stochastic method of differential evolution with a tabu list to minimize the total annual cost and with the Eco-indicator-99 to evaluate the sustainability of the process. The results show that savings of 5.56% and a reduction of 1.72% in Eco-indicator-99 were achieved with a vapor side stream column in comparison with conventional distillation. On the other hand, with a dividing wall column, savings of 5.02% and reductions of 2.92% in Eco-indicator-99 were achieved. This process is capable of meeting a demand greater than 266 million liters of biojet fuel per year. However, the calculated sale price indicates that this biojet fuel still does not compete with conventional jet fuel produced in Mexico. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd.
ABSTRACT
An approach based on fractal scaling analysis to characterize the organization of the Covid-19 genome sequences is presented in this work. The method is based on a multivariate version of the fractal rescaled range analysis implemented on a sliding window scheme to detect variations of long-range correlations over the genome sequence domains. As a preliminary step, the nucleotide sequence is mapped in a numerical sequence by following a Voss rule, resulting in a multichannel sequence represented as a binary matrix. Fractal correlations, quantified in terms of the Hurst exponent, depending on the region of the sequence, where the Covid-19 genome sequences are predominantly random, with some patches of weak long-range correlations. The analysis shows that the regions of randomness are more abundant in the Covid-19 sequences than in the primitive SARS sequence, which suggests that the Covid-19 virus possesses a more diverse genomic structure for replication and infection. The analysis constrained to the surface glycoprotein region shows that the Covid-19 sequence is less random as compared to the SARS sequence, which indicates that the Covid-19 virus can undergo more ordered replications of the spike protein. The Omicron variation exhibits an interesting pattern with some randomness similarities with the other SARS and the Covid-19 genome sequences. Overall, the results show that the multivariate rescaled range analysis provides a suitable framework to assess long-term correlations hidden in the internal organization of the Covid-19 genome sequence. © 2023
ABSTRACT
The Covid-19 health crisis led to the adaptation of teaching staff to fully online training, which meant that many teachers had to undertake accelerated online teaching training courses. This research focuses on the evaluation of self-perceived effectiveness of a course on online teaching digital tools for university professors in Latin America. A field study was carried out based on the perception of the participants. Three aspects were considered: changes in knowledge (α= 0.962), how able participants felt to use the tools (α=0.873) and satisfaction with various aspects of the course (α= 0.942). A pre-post e-survey was applied. Significant favourable differences were found in self-reported knowledge of tools for content management, collaboration, assessment and online tutoring at the end of the course, with a medium effect size. They perceived themselves to be able to use the tools (mean: 3.68, scale 1-4). Overall satisfaction was also high (3.8, scale 1-4). The results point to the effectiveness of the teacher refresher course for online teaching. Follow-up is recommended to assess the implementation of what has been learned. © 2022 Authors. All rights reserved.
ABSTRACT
Traditionally, food sustainability has been considered solely in the stage of agricultural production. However, globalization, the expansion of the food production industry, and the emergence of supermarket chains that control the retail food market require specific significant changes in supply chains in the food sector and, therefore, we need to address the economic, social, and environmental impacts of these events. On the other hand, social selling has increased rapidly in recent years, with a further boom, following current events related to the coronavirus disease (COVID-19). This explosion of social sales, where there are usually no control and regulation entities, can bring problems associated with mishandling items. In this paper, we expose how Blockchain technology supports the traceability of social sales by validating the data provided by the chain participants such as digital health passports, production and transport data in the sale process;the proposed solution generates recommendations on productmanagement considering the agreements previously made by the network actors. To evaluate the proposed smart contracts, we useHyperledger Caliper, obtaining an average throughput of 12.6 transactions per second and an average latency of 0.3 s for the asset update process. We also use a study case to evaluate the proposed project platform's selling-transport stage using Internet of Things (IoT) sensors. © 2023 Tech Science Press. All rights reserved.
ABSTRACT
Objective: To analyze the learning preferences of university students regarding distance education under the circumstances of the arrival of COVID-19. Method: The research was approached under a quantitative, descriptive and correlational approach, in which through 49 items the technical skills and experience with software tools were known. The population consisted of 900 students from different grades and studying different courses at the Faculty of Political Science and International Relations. Results: A significant relationship was found between learning preferences and technical skills developed by the students. Conclusions: Distance learning preferences by young university students are directed to the use of computers, because through digital media they recognize having a better training and greater help in the use of different software for virtual classrooms. © 2022 Authors. All rights reserved.
ABSTRACT
Consumer clothing presents behaviors defined by pre-established trends and patterns in contemporary societies, and in general the consumption of textile products follows this trend. However, as a result of the COVID-19 pandemic and the restrictions perpetuated as a consequence of it, the consumption of textile products has been affected throughout the world. Under this premise, the objective of this research is to analyze the effect of store images, trust and perceived quality on the habits of the textile consumer in the context of the COVID-19 pandemic, for which, firstly, a review of the literature was carried out regarding the variables of the habits of the textile consumer and their relationship with the store image, trust and perceived quality, for which documents from academic search engines were taken into account, such as Scopus, Web of Science, ResearchGate and Google Scholar. On the other hand, a survey was conducted among textile consumers in Ecuador. The measurement tool was completed by 500 participants. In this way, the survey was conducted virtually through Google Forms and through the use of IBM SPSS software. The sampling technique consisted of convenience sampling. For the specific case of this investigation, it was decided to opt for the use of 500 valid questionnaires. This allowed one to propose a model of structural equations based on constructs associated with reference investigations. The main results of this research confirmed that there is a positive impact of the image of the trusted establishment on the product, as well as a positive impact on the general perceived quality of consumption habits (comparison) and on the effect of the quality of perceived service in consumption habits (planning).
ABSTRACT
Background. Although not validated, cycle threshold (Ct) values from real-time (r)RT-PCR are sometimes used as a proxy for infectiousness to inform public health decision-making. A better understanding of variant-specific viral dynamics, including RNA and infectious virus relationships, is needed to clarify implications for diagnostics and transmission. Methods. Non-hospitalized SARS-CoV-2-infected individuals were recruited <= 5 days post-onset and self-collected nasal swabs daily for two weeks. Sequencing was used to determine variant, an in-house quantitative rRT-PCR targeting N gene was used to produce Ct values and determine RNA load, and cytopathic effect was used to assess the presence or absence of infectious virus (binary outcome). We used a Ct threshold of 30 to define high-Ct (Ct > 30) or low-Ct (Ct <= 30) specimens and assessed the percentage of RNA-positive specimens that had infectious virus;variantspecific percentages were compared by chi2 test. Results. We included 113 and 200 RNA-positive specimens from 18 and 28 Omicron- and Delta-infected participants, respectively;timing of RNA-positive specimen collection was similar in both groups (median = 8d post-onset). Maximum observed RNA levels occurred at median of 5 days post-onset for both variants but were lower for participants with Omicron vs Delta [mean RNA copies/mL = 105.2 vs 107.9]. Despite lower RNA levels, infectious virus was frequently detected for both variants [Omicron: median duration = 4.5d;Delta: median = 6d;p = 0.13]. Omicron specimens with infectious virus had higher Cts vs Delta specimens [mean Ct = 29.9 vs 23.2, p < 0.001]. In high-Ct specimens (Ct > 30;Table), the percentage of specimens with infectious virus was typically higher for Omicron vs Delta, and was significantly higher in adults [27.3% vs 9.5%]. In low-Ct specimens (Ct <= 30), the percentage with infectious virus was similar or higher for Omicron vs Delta, and was significantly higher in children [87.5% vs 53.8%] and in those unvaccinated [94.1% vs 47.4%]. Conclusion. CDC does not recommend the use of Ct values as a proxy for infectiousness. These data further highlight that Ct values may not provide a reliable or consistent proxy for infectiousness across variants.
ABSTRACT
Background. The biological determinants of post-acute sequelae of SARS-CoV-2 infection (PASC), defined as the persistence or recurrence of symptoms not explained by an alternative medical diagnosis, are poorly understood. We assessed viral and immunological determinants during acute SARS-CoV-2 infection for an association with PASC at 4 to 8 months. Methods. From September 2020 to February 2022, symptomatic nonhospitalized individuals with laboratory-confirmed SARS-CoV-2 infection were identified within 5 days of symptom onset. We used anterior nasal biospecimens to measure the magnitude and duration of RNA and infectious viral shedding as well as blood samples to measure soluble markers of inflammation during the acute phase (first 28 days post-enrollment). PASC was defined as self-report of 1 or more COVID-19 attributed symptoms between 4 and 8 months after initial illness. We compared virologic and inflammatory markers, GFAP (a marker of neuronal damage) and neutralizing antibody levels from the acute phase between those with and without PASC using Mann-Whitney U tests or repeated measures mixed effects linear models. Results. Among 71 SARS-CoV-2-positive participants with a completed follow-up visit between 4 to 8 months, we included 69 with virologic data and 61 with inflammatory marker data. Median age was 37 (IQR: 29 to 48) Overall, 16/72 (23%) reported at least one qualifying PASC symptom. Report of PASC was associated with >9 days of RNA shedding (p=0.04);all participants stopped RNA shedding by day 20. During acute illness, those with subsequent PASC had increased levels of INF-alpha, INF-gamma, IP-10, IL-10, and MCP-1;these differences were greatest in the early period and normalized over 2 to 3 weeks post-illness onset. Compared to those without PASC, during the acute illness those with PASC had increased levels of GFAP and decreased levels of neutralizing antibodies but these differences were not statistically significant. Conclusion. We found indications that viral and immunological factors during acute illness may be associated with PASC, suggesting acute immunologic response to SARS-CoV-2 may have longer term effects and play a role in PASC. Further understanding of the clinically significance of these observations is needed.
ABSTRACT
This study is developed in order to determine the educational quality in Colombia during the covid 19 pandemic from the perspective of the student experience. The methodology used is framed towards the quantitative field with a correlational level and a field-non-experimental design. For data collection, the database "Cuarentena COVID 19 Jóvenes” is taken as a reference, which is supplied by the mayor of Medellin. The sample under study consisted of a total of 2058 subjects to whom a questionnaire is applied with 12 questions related to their sociodemographic characteristics, access, and availability for classes in virtual modality, and their perception of the experience in the learning processes during virtuality. For the statistical processing of the information, a descriptive analysis of the data is developed in the first instance, based on the frequency and percentage statistics, to subsequently generate cross tables between the elements related to educational quality in Colombia during the covid 19 pandemic from the perspective of the student experience, and finally an analysis of the correlations between the elements is presented through the Chi-squared test. The whole process is developed through the SPSS statistical software. The results allowed to identify in the first instance a high level of students who took classes in their virtual modality, which had access to the internet (74.9%) and an electronic device (78.6%) that allowed them to access these classes in virtual modality. In turn, students considered in a high level of proportion that virtual classes had impaired the learning experience by 69%. © 2022, Springer Nature Switzerland AG.
ABSTRACT
The purpose of this research proposal was aimed at analyzing the existence of a significantly differential academic performance depending on the class modality: traditional face-to-face vs. remote face-to-face, in students of the psychology program, who were studying the subject of fundamentals of measurement and psychological evaluation in a higher education institution in the city of Barranquilla/Colombia. To achieve this objective, a study framed in the postpositivist paradigm was developed, based on quantitative, non-experimental, correlational, cross-sectional and field research. The sample consisted of 37 students, divided into two groups: Group 1 traditional face-to-face modality: 20 students and Group 2 remote face-to-face modality with an N of 17. For the analysis of the data, the t-test was applied, for independent samples, using the SPSS version 18 statistical package. The results allowed to establish the existence of a significantly higher academic performance that favors the group that studied the subject under the traditional face-to-face modality. Elements that could explain this superior performance under the traditional education format, have to do with low level of adaptability of those involved to this new way of developing the teaching-learning process, alteration and emotional management in the face of this new learning atmosphere, low experience and little preparation of students and the teacher to digital management and connection platforms for the development of classes from face-to-face remote, not having the right tools to be able to work effectively lowers the remote connection. © 2022, Springer Nature Switzerland AG.
ABSTRACT
In recent years, the production and consumption of fossil jet fuel have increased as a consequence of a rise in the number of passengers and goods transported by air. Despite the low demand caused by the coronavirus 2019 pandemic, an increase in the services offered by the sector is expected again. In an economic context still dependent on scarce oil, this represents a problem. There is also a problem arising from the fuel's environmental impact throughout its life cycle. Given this, a promising solution is the use of biojet fuel as renewable aviation fuel. In a circular economy framework, the use of lignocellulosic biomass in the form of sugar-rich crop residues allows the production of alcohols necessary to obtain biojet fuel. The tools provided by process intensification also make it possible to design a sustainable process with low environmental impact and capable of achieving energy savings. The goal of this work was to design an intensified process to produce biojet fuel from Mexican lignocellulosic biomass, with alcohols as intermediates. The process was modeled following a sequence of pretreatment/hydrolysis/fermentation/purification for the biomass-ethanol process, and dehydration/oligomerization/hydrogenation/distillation for ethanol-biojet process under the concept of distributed configuration. To obtain a cleaner, greener, and cheaper process, the purification zone of ethanol was intensified by employing a vapor side stream distillation column and a dividing wall column. Once designed, the entire process was optimized by employing the stochastic method of differential evolution with a tabu list to minimize the total annual cost and with the Eco-indicator-99 to evaluate the sustainability of the process. The results show that savings of 5.56% and a reduction of 1.72% in Eco-indicator-99 were achieved with a vapor side stream column in comparison with conventional distillation. On the other hand, with a dividing wall column, savings of 5.02% and reductions of 2.92% in Eco-indicator-99 were achieved. This process is capable of meeting a demand greater than 266 million liters of biojet fuel per year. However, the calculated sale price indicates that this biojet fuel still does not compete with conventional jet fuel produced in Mexico. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd. © 2022 Society of Chemical Industry and John Wiley & Sons, Ltd.