CheetahKG: A Demonstration for Core-based Top-k Frequent Pattern Discovery on Knowledge Graphs

Knowledge graphs capture the complex relationships among various entities, which can be found in various real world applications, e.g., Amazon product graph, Freebase, and COVID-19. To facilitate the knowledge graph analytical tasks, a system that supports interactive and efficient query processing is always in demand. In this demonstration, we develop a prototype system, CheetahKG, that embeds with our state-of-the-art query processing engine for the top-k frequent pattern discovery. Such discovered patterns can be used for two purposes, (i) identifying related patterns and (ii) guiding knowledge exploration. In the demonstration sessions, the attendees will be invited to test the efficiency and effectiveness of the query engine and use the discovered patterns to analyze knowledge graphs on CheetahKG. © 2022 IEEE.

Comparative Analysis of Different Models for Covid-19 Trend Prediction

The critical situation of Covid-19 in recent years is gradually easing. However, it is still important to keep an eye on predicting future data about the pandemic. In this study, we compared the following three models: Long short-term memory (LSTM), Autoregressive Integrated Moving Average (ARIMA), and Logistic to identify and evaluate the cons and pros with the implementation of python code. The data we used is based on the COVID-19 pandemic data of China from 'Our World in Data'. The experimental results indicated that the Logistic achieved the best prediction performance, i.e, with the optimal RMSE. © 2022 IEEE.

Knowledge management and modern digital transformation of the property management industry in China

Purpose In the current urban and increasingly digital/information era, the service of property management towards residents is of key importance to the well-being of society, which is especially well reflected in its role during the COVID-19 pandemic in China. However, professional knowledge management (KM) has yet to be applied to the daily operation of the property management companies in this sector. The authors posit that introduction of KM concepts to property management at this time would significantly help facilitate the transition of traditional property management towards a higher and more effective value-added service model. From the perspective of KM, this study aims to offer both a theoretical and practical analysis of such a novel business model for companies in the property management industry. Design/methodology/approach Given the current status quo of property management, the authors integrate theories from both KM and information-digital management to qualitatively analyse the challenges and difficulties companies are facing and importantly offer practical suggestions for the centralization, digital-information platform establishment and service innovation. Findings Following the analysis of KM and digital-information modeling, the authors identify three main challenges facing property management services offered in the current digital society including market fragmentation, lack of digital platforms and the absence of a unitary service model. Therefore, the authors propose strategic solutions to resolve these aforementioned problems. Specifically, the authors suggest centralizing property management service, the establishment of a KM-based digital platform and the upgrading of the service model, towards offering a new impetus for the development of companies in property management. Research limitations/implications The authors offer essential guidelines derived from knowledge and information management and explore their implications both from a theoretical, as well as pragmatic/practical perspective that overall would support property management companies' crucial transition from the traditional service model to a more digital-based foundation, and hence, provide a higher value-added service for the residents. Originality/value The current study is one of the first attempts to analyse property management services from the perspective of KM with digital transformation enabling its transition to an information-based internet of things infrastructure. The study not only offers practical guidance to the business of property management but importantly, also contributes to the theoretical underpinnings of KM especially as related to secure serviceability, well-being, security and efficiency of the residential environment by integrating people, place, process and technology.

Stimulating Consumption at Low Budget: Evidence from a Large-Scale Policy Experiment Amid the COVID-19 Pandemic

We use a novel panel with detailed transaction records of more than one million de-identified individuals to study the effect of a large-scale Chinese government-issued digital coupon program on consumer spending. Exploiting a difference-in-differences approach, we find that the digital coupon is highly effective in stimulating consumption. An effective government subsidy of RMB 1 can drive excess spending of RMB 3.4 to RMB 5.8, and the effect persists across multiple coupon issuance waves. In explaining the results, we find that a behavioral model with mental accounting and loss aversion can match the empirical evidence from the field. Our analysis, by illustrating the importance of embedding behavioral factors into the design and implementation of public policy, informs the current debate about cost-effective policy tools to recover the economy.

A narrative review of care for patients on maintenance kidney replacement therapy during the COVID-19 era

COVID-19 has inflicted the whole world since the end of 2019 and may transform the provision of care of kidney replacement therapy (KRT). This narrative review aimed to summarize the impacts of COVID-19 on the continuity of KRT and the strategies healthcare facilities adopted to ensure the accessibility and continuity of the care. Management for KRT patients infected with COVID-19 was not within the scope of this review. We searched online publications in PubMed and Sinomed before November 2020, using search terms "COVID-19", "care", and "kidney replacement therapy". We found that COVID-19 affected the care cascade of KRT, the choice of treatment modalities, and self-care of individuals on maintenance treatment. Healthcare providers adopted the strategies including preventing coronavirus disease 2019 (COVID-19), using telehealth in the care cascade, and patients' health education and psychosocial support. We concluded that the pandemic has challenged the current provision of care and has a profound influence on the convey of renal care. © 2021 Pediatric Medicine.

A magnetic nanoparticle labeled immunochromatography kit for sars-cov-2 infection diagnosis

The novel coronavirus disease (COVID-19) is breaking out and spreading rapidly around the world. There is an urgent need for an accurate and rapid detection method to quickly find infected patients and asymptomatic carriers in order to prevent the spread of the severe acute respiratory syndrome coronavirus [SARS-CoV-2]. In this paper, we designed a test strip which used the principle of double antigen sandwich. Fe3O4 magnetic nanobeads are firstly coupled with specific antibodies, and the S protein of the new coronavirus is used as the coating antigen to capture specific antibodies against the new coronavirus, which is used to detect the virus nucleoprotein of specific antibodies in clinical samples. At the same time, Fe3O4 magnetic nanobeads have unique magnetic properties, which can be used to generate different types of detection signals and simplify the detection process. These results can be judged by color changes and magnetic changes at the test and control lines. Compared with the traditional method, this test strip of Fe3O4 magnetic nanobeads has high sensitivity and can qualitatively detect samples within 15 minutes. The magnetic performance of the magnetic nanobeads can be used to improve the sensitivity of the strip in our further research and product development.

Designing a novel nano-vaccine against SARS-CoV-2

The new coronavirus SARS-CoV-2 has become a global pandemic, which has had a huge impact on the lives of people around the world and has caused huge impacts and losses on global economic development. To now, there is still no effective drug or therapy against coronavirus. A large number of studies have shown that vaccines are the ultimate weapon to eliminate major infectious diseases. The development of new vaccines against new coronaviruses is the best way to prevent new coronavirus infections. In this study, we developed a new vaccine against the new coronavirus by combining our self-developed nano adjuvant loaded with carnosine graphene oxide adjuvant with loaded with CpG molecule and RBD protein antigen. Our results showed that this vaccine can produce high titer anti-SARS-CoV-2 RBD antibody neutralizing SARS-CoV-2 in mice within 2 weeks.

A Rapid and high-sensitive real-time reverse transcription-polymerase chain reaction assay used for the detection of severe acute respiratory syndrome coronavirus 2

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a public health emergency of international concern. Real-time reverse transcription-polymerase chain reaction (RT-PCR) is widely used as the gold standard method for the diagnosis of SARS-CoV-2 infection. However, the reliability of current real-time RT-PCR assays is questioned due to some false-negative reports. In this study, we improved the real-time RT-PCR method based on three target regions (ORF1ab, E, and N) of SARS-CoV-2. Results showed that real-time RT-PCR assays herein could complete detection within one hour after viral RNA preparation and had high sensitivity down to 5 copies of viral RNA. In addition, six clinical specimens were detected to evaluate the availability of this method. Among them, four samples were 3-plex SARS-CoV-2 positive and two were negative by real-time RT-PCR. The sensitivity was 100% (4/4), and specificity was 100% (2/2). These results demonstrate that we develop a rapid and high-sensitive real-time RT-PCR method for SARS-CoV-2 detection, which will be a powerful tool for COVID-19 identification and for monitoring suspected patients.

Clinical characteristics of COVID-19-infected cancer patients: a retrospective case study in three hospitals within Wuhan, China.

BACKGROUND: Cancer patients are regarded as a highly vulnerable group in the current Coronavirus Disease 2019 (COVID-19) pandemic. To date, the clinical characteristics of COVID-19-infected cancer patients remain largely unknown. PATIENTS AND METHODS: In this retrospective cohort study, we included cancer patients with laboratory-confirmed COVID-19 from three designated hospitals in Wuhan, China. Clinical data were collected from medical records from 13 January 2020 to 26 February 2020. Univariate and multivariate analyses were carried out to assess the risk factors associated with severe events defined as a condition requiring admission to an intensive care unit, the use of mechanical ventilation, or death. RESULTS: A total of 28 COVID-19-infected cancer patients were included; 17 (60.7%) patients were male. Median (interquartile range) age was 65.0 (56.0-70.0) years. Lung cancer was the most frequent cancer type (n = 7; 25.0%). Eight (28.6%) patients were suspected to have hospital-associated transmission. The following clinical features were shown in our cohort: fever (n = 23, 82.1%), dry cough (n = 22, 81%), and dyspnoea (n = 14, 50.0%), along with lymphopaenia (n = 23, 82.1%), high level of high-sensitivity C-reactive protein (n = 23, 82.1%), anaemia (n = 21, 75.0%), and hypoproteinaemia (n = 25, 89.3%). The common chest computed tomography (CT) findings were ground-glass opacity (n = 21, 75.0%) and patchy consolidation (n = 13, 46.3%). A total of 15 (53.6%) patients had severe events and the mortality rate was 28.6%. If the last antitumour treatment was within 14 days, it significantly increased the risk of developing severe events [hazard ratio (HR) = 4.079, 95% confidence interval (CI) 1.086-15.322, P = 0.037]. Furthermore, patchy consolidation on CT on admission was associated with a higher risk of developing severe events (HR = 5.438, 95% CI 1.498-19.748, P = 0.010). CONCLUSIONS: Cancer patients show deteriorating conditions and poor outcomes from the COVID-19 infection. It is recommended that cancer patients receiving antitumour treatments should have vigorous screening for COVID-19 infection and should avoid treatments causing immunosuppression or have their dosages decreased in case of COVID-19 coinfection.