شدت و پتانسیل انتقال کرونا در کره جنوبی
سال انتشار: 2020 - تعداد صفحات فایل pdf انگلیسی: 6 - تعداد صفحات فایل doc فارسی: 14
اهداف: ازآنجایی که اولین مورد کروناویروس جدید 2019(کوید-19) در 20 ژانویۀ 2020 در کرۀ شمالی شناسایی شد، تعداد موارد به سرعت افزایش یافت به طوری که تا 6 مارس 2020، منجربه ابتلای6284 مورد و فوت42 نفر شد. اولین تحقیق درمورد گزارش تعداد تکثیر کوید-19 در کرۀ جنوبی را برای بررسی سرعت شیوع بیماری، ارائه می دهیم.
روش کار: موارد روزانۀ تأیید شدۀ کوید-19 در کرۀ جنوبی از منابع عمومی موجود استخراج شد. با استفاده از توزیع تجربی گزارشات دارای تأخیر و شبیه سازی مدل رشد کلی، تعداد تکثیر مؤثر را برمبنای توزیع احتمال گسستۀ فاصلۀ زایشی ارزیابی کردیم.
نتایج: چهار گروه اصلی را شناسایی و تعداد تکثیر را 1.5(1.6-1.4 CI: 95%) برآورد کردیم. به علاوه، نرخ رشد طبیعی 0.6 (0.7، 0.6 CI: 95%) و مقیاس بندی پارامتر رشد 0.8 (0.8،0.7 CI: 95%) برآورد شدند، که نشان-دهندۀ پویایی رشد زیر نمایی کوید-19 می باشد. نرخ مرگ و میر موارد خام در بین مردان (1.1%) در مقایسه با زنان (0.4%) بیشتر است و با افزایش سن افزایش می یابد.
نتیجه گیری: نتایج ما انتقال پایدار اولیۀ کوید-19 در کرۀ جنوبی را نشان می دهد و از اجرای اقدامات فاصله گذاری اجتماعی برای کنترل سریع شیوع بیماری حمایت می کند.
کلمات کلیدی: کروناویروس | کوید-19 | کره | تعداد تکثیر
|مقاله ترجمه شده|
Coopetition and COVID-19: Collaborative business-to-business marketing strategies in a pandemic crisis
Coopetition و COVID-19: استراتژی های مشارکتی بازاریابی از کسب و کار در یک بحران همه گیر-2020
Although coopetition (simultaneous cooperation and competition) should positively affect company perfor- mance, it is unclear how implementation of these business-to-business marketing strategies can take place during large-scale emergencies. Therefore, guided by resource-based theory and the relational view, this investigation examines how organisations have used coopetition to cope with the novel Coronavirus (COVID-19) pandemic. Key examples include retailers sharing information about stock levels, pharmaceutical organisations working together to develop a vaccine, technological giants collaborating for the greater good, and charities forming alliances for a joint cause. This paper strengthens the extant literature by highlighting the heterogeneity of coopetition strategies that firms can use within a global crisis. Practitioners must balance the risks and rewards of coopetition activities. In turn, they should decide whether to continue to cooperate with their competitors once the pandemic has ended, or resume operating under individualistic business models. This article ends with some future research directions.
Keywords: Coopetition | Coronavirus | COVID-19 | Business-to-business marketing
Navigating disruptive crises through service-led growth: The impact of COVID-19 on Italian manufacturing firms
هدایت بحران های مخرب از طریق رشد خدمات محور: تأثیر COVID-19 بر بنگاه های تولیدی ایتالیا-2020
This study draws on an extensive survey and interview data collected during the COVID-19 pandemic. The respondents were executives of industrials firms whose factories, warehouses, and headquarters are located in Northern Italy. This is undoubtedly the European region first and most extensively affected by the pandemic, and the government implemented radical lockdown measures, banning nonessential travel and mandating the shutdown of all nonessential businesses. Several major effects on both product and service businesses are highlighted, including the disruption of field-service operations and supply networks. This study also highlights the increased importance of servitization business models and the acceleration of digital transformation and advanced services. To help firms navigate through the crisis and be better positioned after the pandemic, the authors present a four-stage crisis management model (calamity, quick & dirty, restart, and adapt), which provides insights and critical actions that should be taken to cope with the expected short and long-term implications of the crisis. Finally, this study discusses how servitization can enhance resilience for future crises—providing a set of indicators on the presumed role of, and impact on, service operations in relation to what executives expect to be the “next normal.”
Keywords: COVID-19 | Coronavirus | Servitization | Digitalization | Service operations | Solutions | Resilience
Explainable AI and Mass Surveillance System-Based Healthcare Framework to Combat COVID-19 Like Pandemics
چارچوب بهداشتی مبتنی بر سیستم نظارت گسترده و هوش مصنوعی برای مبارزه با COVID-19 مانند موارد همه گیر-2020
Tactile edge technology that focuses on 5G or beyond 5G reveals an exciting approach to control infectious diseases such as COVID-19 internationally. The control of epidemics such as COVID-19 can be managed effectively by exploiting edge computation through the 5G wireless connectivity network. The implementation of a hierarchical edge computing system provides many advantages, such as low latency, scalability, and the protection of application and training model data, enabling COVID-19 to be evaluated by a dependable local edge server. In addition, many deep learning (DL) algorithms suffer from two crucial disadvantages: first, training requires a large COVID-19 dataset consisting of various aspects, which will pose challenges for local councils; second, to acknowledge the outcome, the findings of deep learning require ethical acceptance and clarification by the health care sector, as well as other contributors. In this article, we propose a B5G framework that utilizes the 5G network’s low-latency, high-bandwidth functionality to detect COVID-19 using chest X-ray or CT scan images, and to develop a mass surveillance system to monitor social distancing, mask wearing, and body temperature. Three DL models, ResNet50, Deep tree, and Inception v3, are investigated in the proposed framework. Furthermore, blockchain technology is also used to ensure the security of healthcare data.
Investigating the emerging COVID-19 research trends in the field of business and management: A bibliometric analysis approach
بررسی روندهای نوظهور تحقیق COVID-19 در زمینه تجارت و مدیریت: رویکرد تجزیه و تحلیل کتاب سنجی-2020
The COVID-19 pandemic has been labeled as a black swan event that caused a ripple eﬀect on every aspect of human life. Despite the short time span of the pandemic—only four and half months so far—a rather large volume of research pertaining to COVID-19 has been published (107 articles indexed in Scopus and the Web of Science). This article presents the ﬁndings of a bibliometric study of COVID-19 literature in the business and management domain to identify current areas of research and propose a way forward. The analysis of the published literature identiﬁed four main research themes and 18 sub-themes. The ﬁndings and propositions of this study suggest that COVID-19 will be the catalyst of several long- and short-term policy changes and requires the theoretical and empirical attention of researchers. The oﬀered propositions will act as a roadmap to potential research opportunities.
Keywords: COVID-19 | Emerging research topics | Business & management | Bibliometric analysis | Co-word analysis
Considerations for development and use of AI in response to COVID-19
ملاحظاتی برای توسعه و استفاده از هوش مصنوعی در پاسخ به COVID-19-2020
Artificial intelligence (AI) is playing a key supporting role in the fight against COVID-19 and perhaps will contribute to solutions quicker than we would otherwise achieve in many fields and applications. Since the outbreak of the pandemic, there has been an upsurge in the exploration and use of AI, and other data analytic tools, in a multitude of areas. This paper addresses some of the many considerations for managing the development and deployment of AI applications, including planning; unpredictable, unexpected, or biased results; repurposing; the importance of data; and diversity in AI team membership. We provide implications for research and for practice, according to each of the considerations. Finally we conclude that we need to plan and carefully consider the issues associated with the development and use of AI as we look for quick solutions.
Keywords: Artificial intelligence | AI | Machine learning | COVID-19 | Coronavirus | AI applications | Strategy | Bias | Repurposed AI | Data | Team diversity
The AI-discovered aetiology of COVID-19 and rationale of the irinotecan+ etoposide combination therapy for critically ill COVID-19 patients
اتیولوژی هوش مصنوعی COVID-19 و منطق درمان ترکیبی irinotecan + etoposide برای بیماران COVID-19 که به شدت بیمار هستند کشف شده است-2020
We present the AI-discovered aetiology of COVID-19, based on a precise disease model of COVID-19 built under five weeks that best matches the epidemiological characteristics, transmission dynamics, clinical features, and biological properties of COVID-19 and consistently explains the rapidly expanding COVID-19 literature. We present that SARS-CoV-2 implements a unique unbiased survival strategy of balancing viral replication with viral spread by increasing its dependence on (i) ACE2-expressing cells for viral entry and spread, (ii) PI3K signaling in ACE2-expressing cells for viral replication and egress, and (iii) viral- non-structural-and-accessory-protein-dependent immunomodulation to balance viral spread and viral replication. We further propose the combination of irinotecan (an in-market topoisomerase I inhibitor) and etoposide (an in-market topoisomerase II inhibitor) could potentially be an exceptionally effective treatment to protect critically ill patients from death caused by COVID-19-specific cytokine storms triggered by sepsis, ARDS, and other fatal comorbidities
Keywords: Aetiology | Treatment | Cytokine storm | ICU | COVID-19 | ACE2 Irinotecan | Etoposide | SARS-CoV-2
AI governance in the public sector: Three tales from the frontiers of automated decision-making in democratic settings
حکمرانی هوش مصنوعی در بخش عمومی: سه داستان از مرزهای تصمیم گیری خودکار در تنظیمات دموکراتیک-2020
The rush to understand new socio-economic contexts created by the wide adoption of AI is justified by its far-ranging consequences, spanning almost every walk of life. Yet, the public sector’s predicament is a tragic double bind: its obligations to protect citizens from potential algorithmic harms are at odds with the temptation to increase its own efficiency - or in other words - to govern algorithms, while governing by algorithms. Whether such dual role is even possible, has been a matter of debate, the challenge stemming from algorithms’ intrinsic properties, that make them distinct from other digital solutions, long embraced by the governments, create externalities that rule-based programming lacks. As the pressures to deploy automated decision making systems in the public sector become prevalent, this paper aims to examine how the use of AI in the public sector in relation to existing data governance regimes and national regulatory practices can be intensifying existing power asymmetries. To this end, investigating the legal and policy instruments associated with the use of AI for strenghtening the immigration process control system in Canada; “optimising” the employment services” in Poland, and personalising the digital service experience in Finland, the paper advocates for the need of a common framework to evaluate the potential impact of the use of AI in the public sector. In this regard, it discusses the specific effects of automated decision support systems on public services and the growing expectations for governments to play a more prevalent role in the digital society and to ensure that the potential of technology is harnessed, while negative effects are controlled and possibly avoided. This is of particular importance in light of the current COVID-19 emergency crisis where AI and the underpinning regulatory framework of data ecosystems, have become crucial policy issues as more and more innovations are based on large scale data collections from digital devices, and the real-time accessibility of information and services, contact and relationships between institutions and citizens could strengthen – or undermine - trust in governance systems and democracy.
Keywords: Artificial intelligence | Public sector innovation | Automated decision making | Algorithmic accountability
Are your IT staff ready for the pandemic-driven insider threat?
آیا کارکنان IT شما برای تهدیدات داخلی همه گیر محور آماده هستند؟-2020
As this article is being written it’s mid-March. The situation likely will have changed significantly by the time you read this, as it does by the day and even the hour. The World Health Organisation (WHO) has declared Covid-19 to be a global pandemic and the UK Government has stepped up its response from the ‘contain’ to the ‘delay’ phase. Public spaces and transport are noticeably quieter and many workplaces are getting emptier as staff members work from home.
Scottish mental health and capacity law: The normal, pandemic and ‘new normal’
بهداشت روانی و قانون ظرفیت اسکاتلند: نرمال ، همه گیر و عادی جدید-2020
A states real commitment to its international human rights obligations is never more challenged than when it faces emergency situations. Addressing actual and potential resourcing pressures arising from the COVID-19 pandemic has resulted in, amongst other things, modifications to Scottish mental health and capacity law and the issuing of new guidance relating to associated practice. Whether these emergency or ordinary measures are invoked during the crisis there are potential implications for the rights of persons with mental illness, learning disability and dementia notably those relating to individual autonomy and dignity. This article will consider areas of particular concern but how strict adherence to the legal, ethical and human rights framework in Scotland will help to reduce the risk of adverse consequences.
Keywords: COVID-19 | Scotland | Mental health and capacity law | Emergency measures | Human rights