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1.
Frontiers in Medicine ; 9:914732, 2022.
Article in English | MEDLINE | ID: covidwho-2022766

ABSTRACT

Background: The coronavirus disease 2019 (COVID-19) is a severe acute respiratory disease that poses a continuous threat to global public health. Many non-pharmacological interventions (NPIs) have been implemented to control the COVID-19 pandemic since the beginning. The aim of this study was to assess the impact of various NPIs on COVID-19 mortality during pre-vaccination and vaccination periods. Methods: The COVID-19 data used in this study comes from Our World in Data, we used the Oxford Strict Index (OSI) and its five combination interventions as independent variables. The COVID-19 mortality date (MRT) was defined as a date when daily rate of 0.02 COVID-19 deaths per 100,000 population in a country was reached, and the COVID-19 vaccination date (VRT) was defined as people vaccinated reaching 70%. Linear regression and random forest models were used to estimate the impact of various NPI implementation interventions during pre-vaccination and vaccination periods. The performance of models was assessed among others with Shapley Additive Explanations (SHAP) explaining the prediction capability of the model. Results: During the pre-vaccination period, the various NPIs had strong protective effect. When the COVID-19 MRT was reached, for every unit increase in OSI, the cumulative mortality as of June 30, 2020 decreased by 0.71 deaths per 100,000 people. Restrictions in travel (SHAP 1.68) and cancelation of public events and gatherings (1.37) had major reducing effect on COVID-19 mortality, while staying at home (0.26) and school and workplace closure (0.26) had less effect. Post vaccination period, the effects of NPI reduced significantly: cancelation of public events and gatherings (0.25), staying at home (0.22), restrictions in travel (0.14), and school and workplace closure (0.06). Conclusion: Continued efforts are still needed to promote vaccination to build sufficient immunity to COVID-19 in the population. Until herd immunity is achieved, NPI is still important for COVID-19 prevention and control. At the beginning of the COVID-19 pandemic, the stringency of NPI implementation had a significant negative association with COVID-19 mortality;however, this association was no longer significant after the vaccination rate reached 70%. As vaccination progresses, "cancelation of public events and gatherings" become more important for COVID-19 mortality.

2.
Nature Machine Intelligence ; 2022.
Article in English | Scopus | ID: covidwho-2016856

ABSTRACT

Single-cell datasets continue to grow in size, posing computational challenges for dealing with expanded scale, extended modality and inevitable batch effects. Deep learning-based approaches have recently emerged to address these points by deriving nonlinear cell embeddings. Here we present contrastive learning of cell representations, Concerto, which leverages a self-supervised distillation framework to model multimodal single-cell atlases. Simply by discriminating each cell from the others, Concerto can be adapted to various downstream tasks such as automatic cell type classification, data integration and especially reference mapping. Unlike current mainstream packages, Concerto’s contrastive setting well supports operating on all genes to preserve biological variations. Concerto can flexibly generalize to multiomics to obtain unified cell representations. Benchmarking on both simulated and real datasets, Concerto substantially outperforms competing methods. By mapping to a comprehensive reference, Concerto recapitulates differential immune responses and discovers disease-specific cell states in patients with COVID-19. Concerto is easily parallelizable and efficiently scalable to build a 10-million-cell reference within 1.5 h and query 10,000 cells within 8 s. Overall, Concerto will facilitate biomedical research by enabling iteratively constructing single-cell reference atlases and rapidly mapping novel dataset against them to transfer relevant cell annotations. © 2022, The Author(s), under exclusive licence to Springer Nature Limited.

3.
17th International Conference on Ph.D Research in Microelectronics and Electronics, PRIME 2022 ; : 181-184, 2022.
Article in English | Scopus | ID: covidwho-1981394

ABSTRACT

Low-resolution infrared (IR) Sensors combined with machine learning (ML) can be leveraged to implement privacy-preserving social distance monitoring solutions in indoor spaces. However, the need of executing these applications on Internet of Things (IoT) edge nodes makes energy consumption critical. In this work, we propose an energy-efficient adaptive inference solution consisting of the cascade of a simple wake-up trigger and a 8-bit quantized Convolutional Neural Network (CNN), which is only invoked for difficult-to-classify frames. Deploying such adaptive system on a IoT Microcontroller, we show that, when processing the output of a 8 × 8 low-resolution IR sensor, we are able to reduce the energy consumption by 37-57% with respect to a static CNN-based approach, with an accuracy drop of less than 2% (83% balanced accuracy). © 2022 IEEE.

4.
Hellenic Journal of Radiology ; 7(2):2-7, 2022.
Article in English | Scopus | ID: covidwho-1955556

ABSTRACT

Introduction: Ultrasound guided sampling (USGS) of supraclavicular lymph nodes (SCLN) is a minimally invasive method for obtaining cytological diagnosis in metastatic lung cancer. Same day USGS service may improve timeliness of investigations, minimise hospital visits and reduce invasive procedures. Methods: We performed a 3-year retrospective analysis of patients with SCLN amenable to biopsy detect-ed on 2 week-wait (2WW) CT. We identified those who underwent USGS or other procedures, diagnostic yield and their timeliness were determined. Results: 49 patients (26%) had amenable SCLN, of whom 37 (75.5%) had USGS. USGS alone sufficient for 27 (73%) patients. Diagnostic yield is better for larger nodes (<1cm 62.5% positive;≥1cm 86.2% positive, 95% CI 0.13-0.93, p=0.011). The overall diagnostic yield of USGS SCLN was 81% (30/37, 95% CI 65% to 92%). Al-though faster to obtain USGS, no statistically significant difference was reached between USGS and other methods (USGS median 15.5 days (IQR 11.2), other procedures median 17.5 days (IQR 26.5), Mann-Whitney U p=0.42). Conclusion: USGS SCLN has potential utility in early lung cancer diagnosis, even in lymph nodes <1cm, and is an underutilized diagnostic investigation. A prospective study of same day 2WW outpatient clinic and USGS procedure is now required to assess its effect on an accelerated diagnostic pathway. © 2022, Zita Medical Managent. All rights reserved.

5.
Journal of Industrial and Management Optimization ; 0(0):16, 2022.
Article in English | English Web of Science | ID: covidwho-1884492

ABSTRACT

A painful lesson got from pandemic COVID-19 is that preventive healthcare service is of utmost importance to governments since it can make massive savings on healthcare expenditure and promote the welfare of the society. Recognizing the importance of preventive healthcare, this research aims to present a methodology for designing a network of preventive healthcare facilities in order to prevent diseases early. The problem is formulated as a bilevel non-linear integer programming model. The upper level is a facility location and capacity planning problem under a limited budget, while the lower level is a user choice problem that determines the allocation of clients to facilities. A genetic algorithm (GA) is developed to solve the upper level problem and a method of successive averages (MSA) is adopted to solve the lower level problem. The model and algorithm is applied to analyze an illustrative case in the Sioux Falls transport network and a number of interesting results and managerial insights are provided. It shows that solutions to medium-scale instances can be obtained in a reasonable time and the marginal benefit of investment is decreasing.

6.
Journal of Chinese Economic and Business Studies ; : 21, 2022.
Article in English | Web of Science | ID: covidwho-1852792

ABSTRACT

China has announced its commitment to achieving carbon neutrality by 2060, and for this challenging goal to be reached within just four decades, there is a real urgency of shaping the low-carbon agenda in its 14th Five-Year Plan and to ratchet up ambition on climate policy in the near term to peak emissions early. This paper argues that China will have to change the way of development by take a sustainable pathway to growth. And this new approach does not mean sacrificing economic growth;quite the opposite, it can boost growth by providing great opportunities in terms of jobs, efficiency, demand, and many other aspects, while reducing carbon emissions and enabling great benefits with regards to pollution, ecological restoration, biodiversity and well-beings. The COVID-19 pandemic has provided a window of opportunity for China and other countries to cooperate to link the post-pandemic economic recovery with the fight against climate change.

7.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333697

ABSTRACT

Rapid and sensitive diagnostics of infectious diseases is an urgent and unmet need as evidenced by the COVID-19 pandemic. Here we report a novel strategy, based on DIgitAl plasMONic nanobubble Detection (DIAMOND), to address these gaps. Plasmonic nanobubbles are transient vapor bubbles generated by laser heating of plasmonic nanoparticles and allow single-particle detection. Using gold nanoparticles labels and an optofluidic setup, we demonstrate that DIAMOND achieves a compartment-free digital counting and works on homogeneous assays without separation and amplification steps. When applied to the respiratory syncytial virus diagnostics, DIAMOND is 150 times more sensitive than commercial lateral flow assays and completes measurements within 2 minutes. Our method opens new possibilities to develop single-particle digital detection methods and facilitate rapid and ultrasensitive diagnostics. ONE SENTENCE SUMMARY: Single-particle digital plasmonic nanobubble detection allows rapid and ultrasensitive detection of viruses in a one-step homogeneous assay.

8.
IEEE Transactions on Learning Technologies ; 2022.
Article in English | Scopus | ID: covidwho-1731043

ABSTRACT

During the COVID-19 pandemic, many students lost opportunities to explore science in labs due to school closures. Remote labs provide a possible solution to mitigate this loss. However, most remote labs to date are based on a somehow centralized model in which experts design and conduct certain types of experiments in well-equipped facilities, with a few options of manipulation provided to remote users. In this paper, we propose a distributed framework, dubbed remote labs 2.0, that offers the flexibility needed to build an open platform to support educators to create, operate, and share their own remote labs. Similar to the transformation of the Web from 1.0 to 2.0, remote labs 2.0 can greatly enrich experimental science on the Internet by allowing users to choose and contribute their subjects and topics. As a reference implementation, we developed a platform branded as Telelab. In collaboration with a high school chemistry teacher, we conducted remote chemical reaction experiments on the Telelab platform with two online classes. Pre/post-test results showed that these high school students attained significant gains (t(26)=8.76, p<0.00001) in evidence-based reasoning abilities. Student surveys revealed three key affordances of Telelab: live experiments, scientific instruments, and social interactions. All 31 respondents were engaged by one or more of these affordances. Students behaviors were characterized by analyzing their interaction data logged by the platform. These findings suggest that appropriate applications of remote labs 2.0 in distance education can, to some extent, reproduce critical effects of their local counterparts on promoting science learning. IEEE

10.
Journal of Practical Oncology ; 37(1):82-86, 2022.
Article in Chinese | Scopus | ID: covidwho-1698670

ABSTRACT

Objective: To analyze and summarize the effective management measures for the prevention of COVID-19 infection during outpatient radiotherapy in general hospitals. Method: Based on the requirements of pandemic prevention and control, combined with the possible problems during diagnosis and treatment process in the radiotherapy outpatient of the First Medical Center of Chinese PLA General Hospital, the prevention and control measures such as process adjustment, environmental zoning, protection control and disinfection were retrospectively reviewed under the prevalence of COVID-19, and the effectiveness of the prevention and control was evaluated. Results: The targeted protective measures were taken during outpatient radiotherapy. Through strengthening the entrance management, strict escort management and appointment treatment, a pandemic prevention and control model for outpatient radiotherapy was summarized during the COVID-19 pandemic. A total of 1 959 patients were admitted to our medical center from January to December 2020. All of them accepted radiotherapy and no infection was found among patients and medical personnel, achieving good prevention and control effects. Conclusions: During the COVID-19 pandemic, effective preventative management measures must be taken for the treatment process, the environment, and the personnel in the radiotherapy outpatient clinics of general hospitals, so as to minimize the medical risk of infection, ensure the safety of the medical personnel and patients, and ensure the safe and orderly work of outpatient radiotherapy. © 2022, The Second Affiliated Hospital, College of Medicine, Zhejiang University.. All right reserved.

11.
Journal of Geo-Information Science ; 23(2):236-245, 2021.
Article in Chinese | Scopus | ID: covidwho-1639184

ABSTRACT

Since the outbreak of COVID-19, countries around the world have shown different time-series characteristics. Studying the characteristics of the development patterns of different countries and revealing the dominant factors behind them can provide references for future prevention and control strategies. In order to reveal the similarities and differences between the epidemic time series in different countries, this article extracts the standard deviation, Hurst index, cure rate, growth time, average growth rate, and prevention and control efficiency of the daily time series of new cases in the main epidemic countries for pedigree clustering. We also analyzes the causes of clustering results from the aspects of economics, medical treatment, and humanistic conflicts. The results show that the global epidemic development model can be divided into three categories: C-type, S-type, and I-type. The time series of C-type countries are characterized by continuous fluctuations and rising, and the cure rate is low. The reason is that humanistic conflicts are not conducive to epidemic prevention and control. Economic and medical resources have become scarce after a long period of large consumption. It is recommended to strengthen publicity and guidance in prevention and control, change concepts, and coordinate the allocation of economic and medical resources. The time series of S-type countries is characterized by a rapid rise and then an immediate decline, and eventually maintains a stable trend. The overall cure rate is relatively high. The reason is that these countries have domestic stability, high economic and medical standards, and timely prevention and control measures. It is recommended to strengthen international cooperation and scientific research, and prepare for the possible second epidemic. The time series of I-shaped countries is characterized by a slow rise, the overall development trend is unstable, and the cure rate is low. The reason is that its outbreak is relatively late and less severe. Most of the economic and medical levels and humanistic conflicts are not conducive to epidemic prevention and control. It is recommended to learn better prevention and control experience, implement strict isolation measures, try to meet the material needs during the epidemic, and optimize treatment methods. 2021, Science Press. All right reserved.

12.
Clin Radiol ; 77(2): 148-155, 2022 02.
Article in English | MEDLINE | ID: covidwho-1611681

ABSTRACT

AIM: To determine if there is a difference in radiological, biochemical, or clinical severity between patients infected with Alpha-variant SARS-CoV-2 compared with those infected with pre-existing strains, and to determine if the computed tomography (CT) severity score (CTSS) for COVID-19 pneumonitis correlates with clinical severity and can prognosticate outcomes. MATERIALS AND METHODS: Blinded CTSS scoring was applied to 137 hospital patients who had undergone both CT pulmonary angiography (CTPA) and whole-genome sequencing of SARS-CoV-2 within 14 days of CTPA between 1/12/20-5/1/21. RESULTS: There was no evidence of a difference in imaging severity on CTPA, viral load, clinical parameters of severity, or outcomes between Alpha and preceding variants. CTSS on CTPA strongly correlates with clinical and biochemical severity at the time of CTPA, and with patient outcomes. Classifying CTSS into a binary value of "high" and "low", with a cut-off score of 14, patients with a high score have a significantly increased risk of deterioration, as defined by subsequent admission to critical care or death (multivariate hazard ratio [HR] 2.76, p<0.001), and hospital length of stay (17.4 versus 7.9 days, p<0.0001). CONCLUSION: There was no evidence of a difference in radiological severity of Alpha variant infection compared with pre-existing strains. High CTSS applied to CTPA is associated with increased risk of COVID-19 severity and poorer clinical outcomes and may be of use particularly in settings where CT is not performed for diagnosis of COVID-19 but rather is used following clinical deterioration.


Subject(s)
COVID-19/diagnostic imaging , Computed Tomography Angiography , SARS-CoV-2/genetics , Severity of Illness Index , Whole Genome Sequencing , Aged , COVID-19/mortality , COVID-19/virology , Cohort Studies , Critical Care , Female , Humans , Length of Stay , Male , Middle Aged , Retrospective Studies , Time Factors , United Kingdom , Viral Load
13.
European Heart Journal ; 42(SUPPL 1):238, 2021.
Article in English | EMBASE | ID: covidwho-1553974

ABSTRACT

Background: Cardiac magnetic resonance (CMR) and cardiopulmonary exercise testing (CPET) have provided important insights into the prevalence of early cardiopulmonary abnormalities in COVID-19 patients. It is currently unknown whether such abnormalities persist over time and relate to ongoing symptoms. Purpose: To describe the longitudinal trajectory of cardiopulmonary abnormalities on CMR and CPET in moderate to severe COVID-19 patients and assess their relationship with ongoing symptoms. Methods: Fifty-eight previously hospitalised COVID-19 patients and 30 age, sex, body mass index, comorbidity-matched controls underwent CMR, CPET and a symptom-based questionnaire at 2-3 months (2-3m). Repeat assessments (including gas transfer) were performed in 46 patients at 6 months (6m). Results: During admission, 1/3rd of patients needed ventilation or intensive care (Table 1) and three (5%) had a raised troponin. On CMR, patients had preserved left (LV) and right ventricular (RV) volumes and function at 2-3m from infection. By 6m, LV function did not change but RV end diastolic volume decreased (mean difference -4.3 mls/m2, p=0.005) and RV function increased (mean difference +3.2%, p<0.001, Fig. 1A). Patients had higher native T1 (a marker of fibroinflammation) at 2-3m compared to controls (Table 1, Fig. 1B), which normalised by 6m. Extracellular volume was normal and improved by 6m. Native T2, a marker of myocardial oedema, did not differ between patients and controls on serial CMR. At 2- 3m, late gadolinium enhancement (LGE) was higher in patients (p=0.023) but became comparable to controls by 6m (p=0.62). Six (12%) patients had LGE in a myocarditis pattern and one (2%) had myocardial infarction. None had active myocarditis using the Modified Lake Louise Criteria. Lung imaging (T2-weighted) revealed parenchymal abnormalities in 2/3rds of patients at 2-3 and 6 months. The extent of abnormalities improved on serial imaging (Table 1). Gas transfer (DLco) was worse in those with lung abnormalities (77% vs 91% of predicted, p=0.009). CPET revealed reduced peak oxygen consumption (pVO2) in patients at 2-3m, which normalised by 6m (80.5% to 93.3% of predicted, p=0.001) (Table 1, Fig. 1C). At 2-3m, 49% of patients had submaximal tests (respiratory exchange ratio <1.1), reducing to 25% by 6m (p=0.057). VE/VCO2 slope, a marker of lung efficiency, was abnormal in patients but improved on serial CPET (Table 1, Fig. 1D). Cardiac symptoms (chest pain, dyspnoea, palpitations, dizziness or syncope) were present in 83% of patients at 2-3m, reducing to 52% by 6m (p<0.001). There was no significant association between CMR or CPET parameters and persistent cardiac symptoms at 6m (Fig. 1E). Conclusions: Cardiopulmonary parameters (on CMR and CPET) improved in moderate-severe COVID-19 patients from 2-3 to 6 months post infection. Despite this, patients continued to experience cardiac symptoms which had no relationship with measured parameters. (Figure Presented).

15.
Zhonghua Liu Xing Bing Xue Za Zhi ; 42(8): 1347-1352, 2021 Aug 10.
Article in Chinese | MEDLINE | ID: covidwho-1468521

ABSTRACT

Objective: To analyze the sensitivity and specificity of SARS-CoV-2 nucleic acid testing in 20 348 close contacts of COVID-19 cases in different prevention and control stages in Guangzhou and to provide scientific evidence for optimizing epidemic response strategies. Methods: A total of 20 348 close contacts of COVID-19 cases in Guangzhou were traced between February 21 and September 22,2020. All the close contacts were tested for the nucleic acid of SARS-CoV-2. The sensitivity and specificity of nucleic acid testing and diagnosis in the different prevention and control stages were compared. Results: In 20 348 close contacts, 12 462 were males (61.24%), the median (P25,P75) of age of them was 31.0 years (23.0,43.0), the median number (P25,P75) of nucleic acid testing for them was 2.0 (1.0,3.0), and the median (P25,P75) of their quarantine days was 12.0 (8.0,13.0) days, respectively. A total of 256 COVID-19 cases were confirmed in the close contacts after seven nucleic acid tests. In the 1st, 2nd, 3rd and 7th nucleic acid testing, the sensitivity and specificity were 69.14% and 99.99% (177 cases confirmed), 89.84% and 99.99% (230 cases confirmed), 97.27% and 99.99% (249 cases confirmed), and 100.00% and 99.98%, respectively. In the three stages of COVID-19 prevention and control in China: domestic case stage, imported case stage, and imported case associated local epidemic stage, the sensitivity of the 1st nucleic acid testing was 70.68%, 68.00% and 67.35%, and the specificity was 99.98%, 100.00% and 100.00%, respectively. Conclusions: The sensitivity of nucleic acid testing in the close contacts at the different stages were consistent with slight decrease, which might be related to the increased proportion of asymptomatic infections in the late stage of epidemic prevention and control with COVID-19 in Guangzhou. It is suggested to give three nucleic acid tests to improve the sensitivity and reduce false negative risk.


Subject(s)
COVID-19 , Nucleic Acids , Adult , Asymptomatic Infections , Humans , Male , SARS-CoV-2 , Sensitivity and Specificity
16.
Chinese Automation Congress (CAC) ; : 1614-1618, 2020.
Article in English | Web of Science | ID: covidwho-1398269

ABSTRACT

Corona Virus Disease 2019 (COVID-19) has seriously threatened human life and health in just a few months. The global economy, education, transportation and other aspects have been affected. In order to solve the problems caused by COVID-19 as soon as possible, it is important to quickly and accurately confirm whether people are infected. In this paper, we take MultiResUNet as the basic model, introduce a new "Residual block" structure in the encoder part, add Regularization and Dropout to prevent training overfilling, and change the partial activation function. Propose a model suitable for COVID-19 CT image sets, which can automatically segment four parts of COVID-19 CT images (left&right lung, disease and background) by deep learning. The segmentation results are evaluated and the expected results are achieved. It is helpful for medical workers to recognize the infection area quickly.

17.
Heart ; 107(SUPPL 1):A177-A178, 2021.
Article in English | EMBASE | ID: covidwho-1325162

ABSTRACT

Background Evidence suggests that adverse outcomes in COVID-19 may be driven by a cytokine-induced vascular inflammatory response, caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). Aim We aimed to develop a non-invasive method for quantifying cytokine-driven vascular inflammation in patients with acute COVID-19 infection that could allow risk stratification. Methods We developed a platform for rapid development of novel imaging biomarkers of vascular inflammation, by applying quantitative radiotranscriptomics to images from standard Computed Tomography Angiography (CTA). We used this platform to train a radiotranscriptomic signature (C19-RS) from the perivascular space around the aorta and the internal mammary artery, visualized in routine chest CTAs, to best describe cytokine-driven vascular inflammation, defined using transcriptomic profiles from RNA sequencing data from human arterial biopsies. This signature was tested externally in 435 clinically indicated CT pulmonary angiograms (CTPAs) from patients with or without COVID-19 from 3 different geographical regions. Results COVID-19 patients were characterised by significantly higher C19-RS values (adjusted odds ratio of 2.97 [95%CI: 1.43-6.27], p=0.004), while patients infected with the new B.1.1.7 variant (“UK variant”) were also found to have higher C19-RS values compared to those with the original variant, evidence suggestive of higher degrees of vascular inflammation. C19-RS had prognostic value for in-hospital mortality in COVID-19, with hazard ratios of 3.31 ([95%CI: 1.49-7.33], p=0.003) and 2.58 ([95%CI: 1.10-6.05], p=0.028) in two external testing cohorts respectively, after correction for clinical factors and biochemical biomarkers of inflammation (WBC, CRP) and myocardial injury (troponin). Importantly, the corrected HR for in-hospital mortality was 8.24[95%CI: 2.16- 31.36], P=0.002 for those who received no treatment with dexamethasone, but only 2.27[95%CI: 0.69-7.55], p=0.18 in those who received dexamethasone after the test, suggesting that anti-inflammatory treatment may be modifying the natural history of COVID-19 infection by improving outcomes specifically in those patients with high vascular inflammation. Conclusions Our study introduces a new radiotranscriptomic signature, C19-RS, extracted from routine CTPAs, trained to detect cytokine-driven arterial inflammation, and demonstrates that vascular inflammation determined in this way has prognostic value in patients with COVID-19. The “UK variant” leads to higher vascular inflammation measured in this way, and the risk associated with COVID-19 arteritis is modifiable by dexamethasone.

18.
2021 International Conference on Management of Data, SIGMOD 2021 ; : 2614-2627, 2021.
Article in English | Scopus | ID: covidwho-1299241

ABSTRACT

Recently, there has been a pressing need to manage high-dimensional vector data in data science and AI applications. This trend is fueled by the proliferation of unstructured data and machine learning (ML), where ML models usually transform unstructured data into feature vectors for data analytics, e.g., product recommendation. Existing systems and algorithms for managing vector data have two limitations: (1) They incur serious performance issue when handling large-scale and dynamic vector data;and (2) They provide limited functionalities that cannot meet the requirements of versatile applications. This paper presents Milvus, a purpose-built data management system to efficiently manage large-scale vector data. Milvus supports easy-to-use application interfaces (including SDKs and RESTful APIs);optimizes for the heterogeneous computing platform with modern CPUs and GPUs;enables advanced query processing beyond simple vector similarity search;handles dynamic data for fast updates while ensuring efficient query processing;and distributes data across multiple nodes to achieve scalability and availability. We first describe the design and implementation of Milvus. Then we demonstrate the real-world use cases supported by Milvus. In particular, we build a series of 10 applications (e.g., image/video search, chemical structure analysis, COVID-19 dataset search, personalized recommendation, biological multi-factor authentication, intelligent question answering) on top of Milvus. Finally, we experimentally evaluate Milvus with a wide range of systems including two open source systems (Vearch and Microsoft SPTAG) and three commercial systems. Experiments show that Milvus is up to two orders of magnitude faster than the competitors while providing more functionalities. Now Milvus is deployed by hundreds of organizations worldwide and it is also recognized as an incubation-stage project of the LF AI & Data Foundation. Milvus is open-sourced at https://github.com/milvus-io/milvus. © 2021 Owner/Author.

19.
Thorax ; 76(SUPPL 1):A208, 2021.
Article in English | EMBASE | ID: covidwho-1147047

ABSTRACT

Introduction: Ultrasound guided sampling (USGS) of supraclavicular lymph nodes (SCLN) with fine needle aspiration (FNA) or core biopsy is a well established, minimally invasive method for obtaining cytological diagnosis in metastatic lung cancer. It is recommended in the National Lung Cancer Optimal Pathway 'Direct to Biopsy' option for cases where further staging is not required to guide treatment. Re-modelling of the pathway to incorporate 'direct to biopsy' (same day Radiology or Respiratory service) may help improve timeliness of investigations whilst minimising hospital visits and reducing invasive procedures particularly given COVID-19 precautions. Method: We performed a retrospective analysis of patients with SCLN amenable to FNA or biopsy detected on 2 week wait (2WW) CT, timeliness of subsequent SCLN sampling and (Figure presented) diagnostic yield. Data was extracted from InfoFlex from January 2017 to December 2019. Inclusion criteria was at least N2 mediastinal lymphadenopathy >0.5 cm at initial staging with adequate lower neck CT coverage, and where the node was amenable to biopsy (determined by a radiologist). Review of patient records identified those who underwent USGS, whether this was diagnostic and which other procedures were performed. Statistical analysis was performed using IBM SPSS. Results: From 186 patients with suspected N2 or N3 lymphadenopathy at initial staging, 49 (26%) had SCLN amenable to sampling, of whom 37 (75.5%) had sampling performed. Diagnostic yield was 81.2%. Average timeline from 2WW CT to USGS was variable (M = 18 days, 95% CI[14.5, 21.5]) but shorter, on average, compared to other diagnostic procedures (M=22.81 days, 95% CI[13.02, 35.6]). SCLNs with positive biopsy are larger than those without, with AUC of 0.814 (see figure 1). SCLN size of ≥0.65 cm was highly associated with a diagnostic result. Conclusion: 2WW CT with lower neck coverage provided an early opportunity to identify any amenable SCLN especially in the presence of enlarged mediastinal nodes, for ultrasound guided sampling even when SCLN measured <1 cm, and may apply in up to 25% of patients, A prospective study of ultrasound assessment of all patients with N2 mediastinal lymphadenopathy is now required to assess its clinical utility and effect on an accelerated diagnostic pathway.

20.
Current Issues in Tourism ; 2021.
Article in English | Scopus | ID: covidwho-1109078

ABSTRACT

The moderation roles of empathy and perceived waiting time (PWT) on post-pandemic travel intentions have not as yet been investigated. This study of 684 Chinese resident respondents elicited how COVID-19 risk messages affected post-pandemic travel intentions. The results showed that people exposed to messages in the risk-amplifying frame had lower basic travel and destination travel intentions than those who were exposed to messages in the risk- attenuating frame. Empathy had a beneficial effect on basic travel intentions and had an inducing effect on destination travel intentions only in high-risk situations. High PWT tourists had more positive destination travel intentions in the risk-attenuating frame. The findings provide a theoretical basis for future research as well as practical implications for destination risk communications and market restoration during a public health crisis. © 2021 Informa UK Limited, trading as Taylor & Francis Group.

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