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В статье рассмотрен философский аспект развития государственных программ цифровизации разных стран. Дана характеристика категории «искусственный интеллект». Показаны особенности внедрения слабого искусственного интеллекта в социальные системы, в частности, в России, Китае и странах Запада. На примере COVID-19 рассмотрено принятие обществом мер государственного принуждения. Освещены вопросы вмешательства правительств в частную жизнь, влияния искусственного интеллекта на окружающую реальность. Приведены аксиологические основания различий в реакции разных народов на необходимость исполнения распоряжений органов власти.

Why are the epidemic patterns of COVID-19 so different among different cities or countries which are similar in their populations, medical infrastructures, and people's behavior? Why are forecasts or predictions made by so-called experts often grossly wrong, concerning the numbers of people who get infected or die? The purpose of this study is to better understand the stochastic nature of an epidemic disease, and answer the above questions. Much of the work on infectious diseases has been based on "SIR deterministic models," (Kermack and McKendrick:1927.) We will explore stochastic models that can capture the essence of the seemingly erratic behavior of an infectious disease. A stochastic model, in its formulation, takes into account the random nature of an infectious disease. The stochastic model we study here is based on the "birth-and-death process with immigration" (BDI for short), which was proposed in the study of population growth or extinction of some biological species. The BDI process model ,however, has not been investigated by the epidemiology community. The BDI process is one of a few birth-and-death processes, which we can solve analytically. Its time-dependent probability distribution function is a "negative binomial distribution" with its parameter $r$ less than $1$. The "coefficient of variation" of the process is larger than $\sqrt{1/r} > 1$. Furthermore, it has a long tail like the zeta distribution. These properties explain why infection patterns exhibit enormously large variations. The number of infected predicted by a deterministic model is much greater than the median of the distribution. This explains why any forecast based on a deterministic model will fail more often than not. 28 pages, 14 figures

AbstractBackgroundSince the start of the new Coronavirus (COVID-19) outbreak in December 2019, pharmacists worldwide are playing a key role adopting innovative strategies to minimize the adverse impact of the pandemic.ObjectivesTo identify and describe core services provided by the pharmacist during the COVID-19 pandemic.MethodsA literature search was performed in MEDLINE, Embase, Scopus, and LILACS for studies published between December 1st, 2019 and May 20th, 2020 without language restriction. Studies that reported services provided by pharmacists during the COVID-19 pandemic were included. Two independent authors performed study selection and data extraction with a consensus process. The pharmacist’s intervention identified in the included studies were described based on key domains in the DEPICT v.2.ResultsA total of 1,189 records were identified, of which 11 studies fully met the eligibility criteria. Most of them were conducted in the United States of America (n=4) and China (n=4). The most common type of publication were letters (n=4) describing the workplace of the pharmacist in hospitals (n=8). These findings showed the different roles of pharmacists during the COVID-19 pandemic, such as disease prevention and infection control, adequate storage and drug supply, patient care and support for healthcare professionals. Pharmacists’ interventions were mostly conducted for healthcare professionals and patients (n=7), through one-to-one contact (n=11), telephone (n=6) or video conference (n=5). The pharmacists’ main responsibility was to provide drug information for healthcare professionals (n=7) as well as patient counseling (n=8).ConclusionsA reasonable number of studies that described the role of the pharmacists during the COVID-19 pandemic were found. All studies reported actions taken by pharmacists, although without providing a satisfactory description. Thus, future research with more detailed description as well as an evaluation of the impact of pharmacist intervention is needed in order to guide future actions in this and-or other pandemic.

BACKGROUND Patient-centered outcomes research (PCOR) engages patients as partners in research and focuses on questions and outcomes that are important to patients. The COVID-19 pandemic has forced PCOR teams to engage through web-based platforms rather than in person. Similarly, virtual engagement is the only safe alternative for members of the cystic fibrosis (CF) community, who spend their lives following strict infection control guidelines and are already restricted from in-person interactions. In the absence of universal best practices, the CF community has developed its own guidelines to help PCOR teams engage through web-based platforms. OBJECTIVE This study aimed to identify the important attributes, facilitators, and barriers to teams when selecting web-based platforms. METHODS We conducted semistructured interviews with CF community members, nonprofit stakeholders, and researchers to obtain information regarding their experience with using web-based platforms, including the effectiveness and efficiency of these platforms and their satisfaction with and confidence while using each platform. Interviews conducted via Zoom were audio recorded and transcribed. We identified key themes through content analysis with an iterative, inductive, and deductive coding process. RESULTS In total, 15 participants reported using web-based platforms for meetings, project management, document sharing, scheduling, and communication. When selecting web-based platforms, participants valued their accessibility, ease of use, and integration with other platforms. Participants speculated that successful web-based collaboration involved platforms that emulate in-person interactions, recognized the digital literacy levels of the team members, intentionally aligned platforms with collaboration goals, and achieved team member buy-in to adopt new platforms. CONCLUSIONS Successful web-based engagement in PCOR requires the use of multiple platforms in order to fully meet the asynchronous or synchronous goals of the project. This study identified the key attributes for the successful practice of PCOR on web-based platforms and the common challenges and solutions associated with their use. Our findings provide the best practices for selecting platforms and the lessons learned through web-based PCOR collaborations.

Abstract Background Coronaviruses pose a serious threat to global health as evidenced by Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS), and COVID-19. SARS Coronavirus (SARS-CoV), MERS Coronavirus (MERS-CoV), and the novel coronavirus, previously dubbed 2019-nCoV, and now officially named SARS-CoV-2, are the causative agents of the SARS, MERS, and COVID-19 disease outbreaks, respectively. Safe vaccines that rapidly induce potent and long-lasting virus-specific immune responses against these infectious agents are urgently needed. The coronavirus spike (S) protein, a characteristic structural component of the viral envelope, is considered a key target for vaccines for the prevention of coronavirus infection. Methods We first generated codon optimized MERS-S1 subunit vaccines fused with a foldon trimerization domain to mimic the native viral structure. In variant constructs, we engineered immune stimulants (RS09 or flagellin, as TLR4 or TLR5 agonists, respectively) into this trimeric design. We comprehensively tested the pre-clinical immunogenicity of MERS-CoV vaccines in mice when delivered subcutaneously by traditional needle injection, or intracutaneously by dissolving microneedle arrays (MNAs) by evaluating virus specific IgG antibodies in the serum of vaccinated mice by ELISA and using virus neutralization assays. Driven by the urgent need for COVID-19 vaccines, we utilized this strategy to rapidly develop MNA SARS-CoV-2 subunit vaccines and tested their pre-clinical immunogenicity in vivo by exploiting our substantial experience with MNA MERS-CoV vaccines. Findings Here we describe the development of MNA delivered MERS-CoV vaccines and their pre-clinical immunogenicity. Specifically, MNA delivered MERS-S1 subunit vaccines elicited strong and long-lasting antigen-specific antibody responses. Building on our ongoing efforts to develop MERS-CoV vaccines, promising immunogenicity of MNA-delivered MERS-CoV vaccines, and our experience with MNA fabrication and delivery, including clinical trials, we rapidly designed and produced clinically-translatable MNA SARS-CoV-2 subunit vaccines within 4 weeks of the identification of the SARS-CoV-2 S1 sequence. Most importantly, these MNA delivered SARS-CoV-2 S1 subunit vaccines elicited potent antigen-specific antibody responses that were evident beginning 2 weeks after immunization. Interpretation MNA delivery of coronaviruses-S1 subunit vaccines is a promising immunization strategy against coronavirus infection. Progressive scientific and technological efforts enable quicker responses to emerging pandemics. Our ongoing efforts to develop MNA-MERS-S1 subunit vaccines enabled us to rapidly design and produce MNA SARS-CoV-2 subunit vaccines capable of inducing potent virus-specific antibody responses. Collectively, our results support the clinical development of MNA delivered recombinant protein subunit vaccines against SARS, MERS, COVID-19, and other emerging infectious diseases.

Background –The use of gadgets among adolescents has some advantages. There has been a very significant increase in the use of cell phones, especially among teenagers. Gadget addiction will have an impact on social relationships, violent behavior,and mental health disorders. Purpose - This study aims to determine the characteristics of gadget and to determine the frequency distribution of gadget dependency levels. Design / methodology / approach – This study was using descriptive analytic. Samples in this study were adolescents and taken by multi-stage random sampling after being grouped by region. Sample that met the inclusion criteria was 86 respondents. Data collection in this study used an instrument in the form of a Smartphone Addiction Scale (SAS) questionnaire. Findings - The results showed that the highest level of gadget’s addiction in adolescents was low (34.9%), moderate dependence (33.7%), while for high dependence it was 14% and very high dependency 4.7%. 51.7% of male adolescents showed moderate gadget dependence symptoms and 56.7% of female adolescents showed low levels of dependence. Research limitations – This study has limitations, namely that the implementation was planned face-to-face due to the Covid-19 pandemic conditions, the implementation of the research was carried out through the network. Originality / value - This study produces data that is not yet available in the city of Bukittinggi regarding the level of gadget dependence on adolescents in 2020, and can be the basis for further intervention in groups of children with a level of gadget dependence, both for schools, as well as on families and individuals.

In the last century, we have passed two severe pandemics; the 1957 influenza (Asian flu) pandemic and the 1918 influenza (Spanish flu) pandemic with a high fatality rate. In the last few months, we have been again facing a new epidemic (COVID-19), which is a frighteningly high-risk disease and is globally threatening human lives. Among all attempts and presented solutions to tackle the COVID-19, a publicly available dataset of radiological imaging using chest radiography, also called chest X-ray (CXR) images, could efficiently accelerate the detection process of patients infected with COVID-19 through presented abnormalities in their chest radiography images. In this study, we have proposed a deep neural network (DNN), namely RAM-Net, a new combination of MobileNet with Dilated Depthwise Separable Convolution (DDSC), Residual blocks, and Attention augmented convolution. The network has been learned and validated using the COVIDx dataset, one of the most popular public datasets comprising the chest X-ray (CXR) images. Using this model, we could accurately identify the positive cases of COVID-19 viral infection while a new suspicious chest X-ray image is shown to the network. Our network’s overall accuracy on the COVIDx test dataset was 95.33%, with a sensitivity and precision of 92% and 99% for COVID-19 cases, respectively, which are the highest results on the COVIDx dataset to date, to the best of our knowledge. Finally, we performed an audit on RAM-Net based on the Grad-CAM’s interpretation to demonstrate that our proposed architecture detects SARS-CoV-2 (COVID-19) viral infection by focusing on vital factors rather than relying on irrelevant information.

The article presents a rare case of thrombosis of the pulmonary arteries branches, which developed in a patient two months after infection with the SARS-CoV-2 virus, that caused bilateral polysegmental pneumonia. The thrombosis was suspected because of a high plasma D-dimer level. Contrast-enhanced chest CT was performed to make a definitive diagnosis. The absence of blood clots in the veins of the lower extremities and pelvis allowed us to conclude that the patient did not have thromboembolism, but rather a pulmonary thrombosis in situ. Such possible causes of venousthromboembolic complications as tumors, systemic diseases of the connective tissue, and antiphospholipid syndrome were excluded based on negative tests for tumor and autoimmune diseases markers. The long-stay in the hospital was associated with the inability of the patient to maintain the normal level of blood oxygen saturation independently due to the large area of the lung damage associated with COVID-19 pneumonia and ischemia caused by thrombosis of the branches of the pulmonary arteries.

BACKGROUND: The rapid spread of SARS-CoV-2 virus, which caused the COVID-19 pandemic, and the emergence of new co-circulating antigenic variants require the development and update of subtyping kits and protocols. Pyrosequencing-based protocols are promising approach for detection of single nucleotide polymorphisms. AIM: In this study we designed the assays for genotyping Variants of Concern of the SARS-CoV-2 coronavirus using polymerase chain reaction, followed by determination of the virus variant in the sample by pyrosequencing. MATERIALS AND METHODS: Pyrosequencing assays were designed based on alignment of SARS-CoV-2 sequences. Testing was performed using RNA of SARS-CoV-2 viruses of different lineages (alpha, beta, gamma, delta, and omicron). Pyrosequencing was performed using the PyroMark Q24 system. RESULTS: The protocols of sample preparation and pyrosequencing were developed and tested for sequencing of regions encoding substitutions in amino acid positions: L18F, T19R, T20N; A67V, 69-70; G142D, 143-145; 156-157, R158G; 242-244; K417N/T; L452R; S477N, T478K, E484A/K/Q; H655Y; N679K, P681H/R. The specificity of the system was also evaluated in reactions with a negative control sample (RNA isolated from human nasal swab). CONCLUSIONS: In this study, we developed and initially tested protocol for detecting coronavirus variants (alpha, beta, gamma, delta, and omicron) from samples collected from cell culture, based on the PCR technique, followed by genotyping of the variants by pyrosequencing with PyroMark Q24. The developed protocols may be adjusted to the current epidemiological situation by increasing the number of detectable sites.