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Background: Premature infants usually don't have optimal breastfeeding. Given the insufficient awareness and lack of support of mothers can lead to the discontinuation of breastfeeding. The aim of this study was to investigate the effect of telephone monitoring of mothers throughout the breastfeeding period in preterm infants. Method(s): In this quality improvement study,74 mothers with premature infants hospitalized at the NICU, one of the teaching hospitals of Babol University of Medical Sciences in 2020 and their infants were included using random blocking method and divided into intervention and control groups. Breastfeeding Continuation training program after discharge for the intervention group was implemented via smartphone and WhatsApp messenger program during weekly calls for 3 months addressing the problems and challenges faced by breastfeeding mothers. Control group received the usual training at the wards. Data were collected via questionnaire including demographic characteristics of parents and infants, feeding method used and records of infant weight (once a month for 3 months after discharge). Data were analyzed using the Chi-square, T-test, and analysis covariance. Finding(s): Our findings showed that the rate of breastfeeding in intervention group increased from 27% at time of discharge to 86% at third month, while in control group breastfeeding decreased from 24% at time discharge to 19% at third month. This difference was significant. The mean weight of infant in first and second month in intervention group were 3294.59 +/- 574.17, 4577.02 +/- 680.23 and control group 3067.56 +/- 378.08, 4283.78 +/- 508.68, respectively, which was statistically significant. However, this rate was 5856.75 +/- 720.83 and 5663.51 +/- 645.13 in intervention and control groups in third month respectively. There was no overall significant difference. Conclusion(s): Continuing breastfeeding training after discharge using smartphone messaging app can influence success in continuation of breastfeeding by mothers and infant weight gain.Copyright © 2022 Isfahan University of Medical Sciences(IUMS). All rights reserved.
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Notwithstanding the impact that the Coronavirus pandemic has had on the physical and psychological wellness of people, it has also caused a change in the psychological conditions of many employees, particularly among organizations and privately owned businesses, which confronted numerous limitations because of the unique states of the pandemic. Accordingly, the current review expected to implement an RBF neural network to dissect the connection between demographic variables, resilience, Coronavirus, and burnout in start-ups. The examination technique was quantitative. The statistical populace of the review is directors and representatives of start-ups. In view of the statistical sample size of the limitless community, 384 of them were investigated. For information gathering, standard polls incorporating MBI-GS and BRCS and specialist-made surveys of pressure brought about by Coronavirus were utilized. The validity of the polls was affirmed by a board of specialists and their reliability was affirmed by Cronbach's alpha coefficient. The designed network structure had ten neurons in the input layer, forty neurons in the hidden layer, and one neuron in the output layer. The amount of training and test data were 70% and 30%, respectively. The output of the neural network and the collected results were compared with each other, and the designed network was able to classify all the data correctly. Using the method presented in this research can greatly help the sustainability of companies. © 2023 by the authors.
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Background: Premature infants usually don't have optimal breastfeeding. Given the insufficient awareness and lack of support of mothers can lead to the discontinuation of breastfeeding. The aim of this study was to investigate the effect of telephone monitoring of mothers throughout the breastfeeding period in preterm infants.
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In addition to the effect that the COVID-19 pandemic has had on the physical and mental health of individuals, it has also led to a change in the mental and emotional state of many employees. Especially among businesses and private companies, which faced many restrictions due to the special conditions of the pandemic. Therefore, the present study aimed to design an artificial neural network with MLP technique to analyze the relationship between demographic variables, resilience, COVID-19 and burnout in start-ups in Iran. The research method was quantitative. Managers and employees of start-ups formed the statistical population of the study, based on the statistical sample size of the unlimited community, 384 of them were tested. For data gathering, standard questionnaires include of MBI-GS and BRCS and researcher-made questionnaire of stress caused by COVID-19 were used. The validity of the questionnaires was confirmed by a panel of experts and their reliability was confirmed by Cronbach’s alpha coefficient. The number of neurons in the input layer was equal to 10, the number of neurons in the 1st hidden layer was equal to 7, the number of neurons in the output layer was equal to 1, and the number of epochs was equal to 500. 70% of the data were used for training and 30% for testing. In the designed artificial neural network, all experiment data except one were correctly predicted and the obtained MAE error was less than 0.012%. Finally, he precision and correction of the presented model was confirmed by the obtained results. © 2022, Tech Science Press. All rights reserved.
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Personal protective equipment (PPE) is critical to protect against highly infectious diseases such as COVID-19. Textiles are also necessary shields for protecting human skin from ultraviolet (UV) rays. Organic blockers and semiconductor oxides, such as titanium dioxide (TiO2), zinc oxide (ZnO), silicon dioxide (SiO2), etc. can protect against UV rays. Green technologies such as nano, bio, plasma, supercritical CO2, and ultrasonic have emerged to ensure environmental and social compatibility, ensure safety for human health, and replace traditional chemical textile processes. Multifunctional textiles with different impacts such as UV blocking, antimicrobial, self-cleaning, and waterproof qualities can be obtained through green textile treatments. Using these treatments results in almost no waste of water and energy. Green treatments contain degradable chemicals that are not dangerous to either humans or the environment. © 2022 Elsevier Ltd. All rights reserved.
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The Emirates Mars Mission (EMM) is the United Arab Emirates (UAE) first mission to Mars and is the first Arab mission to another planet. It launched an unmanned observatory called "Hope" into an elliptical orbit around Mars on July 20, 2020 carrying three scientific instruments to study the Martian atmosphere in visible, ultraviolet, and infrared wavelengths. EMM will be the first mission to provide the first truly global picture of the Martian atmosphere, revealing important information about how atmospheric processes drive diurnal variations for a period of one Martian year. This will provide scientists with valuable understanding of the changes to the Martian atmosphere today through the achievement of three scientific objectives: A. Characterize the state of the Martian lower atmosphere on global scales and its geographic, diurnal and seasonal variability. B. Correlate rates of thermal and photochemical atmospheric escape with conditions in the collisional Martian atmosphere. C. Characterize the spatial structure and variability of key constituents in the Martian exosphere. The mission is led by Emiratis from Mohammed Bin Rashid Space Centre (MBRSC) and is expanding the nation s human capital through knowledge transfer programs set with international partners from the University of Colorado Laboratory for Atmospheric and Space Physics (LASP), Arizona State University (ASU) School of Earth and Space Exploration, and University of California Berkeley Space Sciences Laboratory (SSL). The paper highlights the driving motivation behind the mission, its scientific objectives and instruments, the unforeseen challenges amid the COVID-19 pandemic, as well as the status and accomplishments of the mission since its Mars Orbit insertion on Feb 9, 2021. © 2021 International Astronautical Federation, IAF. All rights reserved.
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Introduction: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive-sense single-strand RNA virus belonging to the Coronaviridae family, responsible for coronavirus infectious disease 2019 (COVID-19) with the rapid transmission. This study aimed to characterize and compare SARS-CoV-2 and SARS-CoV major viral proteins and predict antigen proteasomal cleavage patterns, MHC class I processing and presentation, and B T-cell and anti-inflammatory epitopes.
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The 2019 novel coronavirus is another type of known coronaviruses;SARS-CoV-1 and MERS-CoV. The World Health Organization (WHO) has named the virus SARS-CoV-2 and its disease as coronavirus disease 2019 (abbreviated COVID-19). The first case of COVID-19 was reported in December 2019 in Wuhan, China. The epidemiological studies have shown that the disease is transmitted from animal to human, and the spread of the disease from person to person is rapidly expanding. Currently, the most important factor in preventing and controlling the spread of the disease is proper recognition, health care, and control measures. Given the importance of early detection and timely treatment of the disease, the use of nanoscale materials for the production of sensors and drug delivery system can be of great assistance to the researchers. In this context, we aimed to explain the effects of the prevalence of the disease worldwide and consider the different aspects of SARS-CoV-2. Copyright © 2021, This is an original open-access article distributed under the terms of the Creative Commons Attribution-noncommercial 4.0 International License which permits copy and redistribution of the material just in noncommercial usages with proper citation.
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Background: The coronavirus disease 2019 (COVID-19) has been associated with a wide range of clinical symptoms. Objectives: The present study aims to investigate the neurological manifestations among patients hospitalized with COVID-19 in Rouhani Hospital in Babol. Methods: This is a descriptive cross-sectional survey conducted in March and April 2020 on patients admitted to Rouhani Hospital in Babol with COVID-19. A number of 230 medical records were selected randomly from a list. The data were collected using the demographic characteristics questionnaire and a checklist for the neurological symptoms. Results: Among the 230 patients with COVID-19 (mean [SD] age, 59.85 [16.22] years;138 men [60%]), 127 (56%) patients had at least one neurologic symptom. The most common symptoms of the central nervous system disorder were headache (34%), dizziness (25%), and impaired consciousness (20%), and the most prevalent symptoms of the peripheral nervous system disorder were taste impairment (17%) and smell impairment (16%). The occurrence of transient ischemic attack (TIA) in women was significantly higher than in men (P = 0.02). Moreover, the incidence of dizziness, impaired consciousness, ataxia, cerebrovascular accident (CVA), anorexia, and smell impairment had a significant relationship with age (P < 0.05). Conclusions: The neurological manifestations are prevalent and substantial among patients with COVID-19. Therefore, it is sug-gested that the healthcare workers take these symptoms seriously, especially in the outbreak of COVID-19, and take the pertinent preventive and protective measures. © 2020, Author(s).