Rainfall Nowcasting by Blending of Radar Data and Numerical Weather Prediction

In order to improve conventional rainfall nowcasting, radar extrapolation and high-resolution numerical weather prediction (NWP) were blended to get a 6-h quantitative precipitation forecast (QPF) over the Yangtze River Delta region of China. Modifications and calibrations were done to both the extrapolation and NWP in order to get an integrated result from the two, which mainly included the extension for the extrapolation time and region, intensity and position calibration for the NWP, weighted blending of extrapolation and NWP based on scale and time, and a final real-time Z-R relation conversion. Forecast experiments were done, and results show that the blending technique could effectively extend forecast time compared with conventional radar extrapolation, meanwhile applying a positive calibration to the NWP. The overall CSI score of 0–6 h reflectivity forecast was better than either single forecast

Promoting Open-domain Dialogue Generation through Learning Pattern Information between Contexts and Responses

Recently, utilizing deep neural networks to build the opendomain dialogue models has become a hot topic. However, the responses generated by these models suffer from many problems such as responses not being contextualized and tend to generate generic responses that lack information content, damaging the user's experience seriously. Therefore, many studies try introducing more information into the dialogue models to make the generated responses more vivid and informative. Unlike them, this paper improves the quality of generated responses by learning the implicit pattern information between contexts and responses in the training samples. In this paper, we first build an open-domain dialogue model based on the pre-trained language model (i.e., GPT-2). And then, an improved scheduled sampling method is proposed for pre-trained models, by which the responses can be used to guide the response generation in the training phase while avoiding the exposure bias problem. More importantly, we design a response-aware mechanism for mining the implicit pattern information between contexts and responses so that the generated replies are more diverse and approximate to human replies. Finally, we evaluate the proposed model (RAD) on the Persona-Chat and DailyDialog datasets; and the experimental results show that our model outperforms the baselines on most automatic and manual metrics

Metallic skeleton promoted two-phase durable icephobic layers

HypothesisThe accretion of ice on component surfaces often causes severe impacts or accidents in modern industries. Applying icephobic surface is considered as an effective solution to minimise the hazards. However, the durability of the current icephobic surface and coatings for long-term service remains a great challenge. Therefore, it is indeed to develop new durable material structures with great icephobic performance.ExperimentsA new design concept of combining robust porous metallic skeletons and icephobic filling was proposed. Nickel/polydimethylsiloxane (PDMS) two-phase layer was prepared using porous Ni foam skeletons impregnated with PDMS as filling material by a two-step method.FindingsGood icephobicity and mechanical durability have been verified. Under external force, micro-cracks could easily initiate at the ice/solid interface due to the small surface cavities and the difference of local elastic modulus between the ice and PDMS, which would promote the ice fracture and thus lead to low ice adhesion strength. The surface morphology and icephobicity almost remain unchanged after water-sand erosion, showing greatly improved mechanical durability. By combining the advantages of the mechanical durability of porous Ni skeleton and the icephobicity of PDMS matrix, the Ni foam/PDMS two-phase layer demonstrates great potentials for ice protection with long-term service time

Analysis of COVID-19 Guideline Quality and Change of Recommendations: A Systematic Review.

Background Hundreds of coronavirus disease 2019 (COVID-19) clinical practice guidelines (CPGs) and expert consensus statements have been developed and published since the outbreak of the epidemic. However, these CPGs are of widely variable quality. So, this review is aimed at systematically evaluating the methodological and reporting qualities of COVID-19 CPGs, exploring factors that may influence their quality, and analyzing the change of recommendations in CPGs with evidence published. Methods We searched five electronic databases and five websites from 1 January to 31 December 2020 to retrieve all COVID-19 CPGs. The assessment of the methodological and reporting qualities of CPGs was performed using the AGREE II instrument and RIGHT checklist. Recommendations and evidence used to make recommendations in the CPGs regarding some treatments for COVID-19 (remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir) were also systematically assessed. And the statistical inference was performed to identify factors associated with the quality of CPGs. Results We included a total of 92 COVID-19 CPGs developed by 19 countries. Overall, the RIGHT checklist reporting rate of COVID-19 CPGs was 33.0%, and the AGREE II domain score was 30.4%. The overall methodological and reporting qualities of COVID-19 CPGs gradually improved during the year 2020. Factors associated with high methodological and reporting qualities included the evidence-based development process, management of conflicts of interest, and use of established rating systems to assess the quality of evidence and strength of recommendations. The recommendations of only seven (7.6%) CPGs were informed by a systematic review of evidence, and these seven CPGs have relatively high methodological and reporting qualities, in which six of them fully meet the Institute of Medicine (IOM) criteria of guidelines. Besides, a rapid advice CPG developed by the World Health Organization (WHO) of the seven CPGs got the highest overall scores in methodological (72.8%) and reporting qualities (83.8%). Many CPGs covered the same clinical questions (it refers to the clinical questions on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir in COVID-19 patients) and were published by different countries or organizations. Although randomized controlled trials and systematic reviews on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir for patients with COVID-19 have been published, the recommendations on those treatments still varied greatly across COVID-19 CPGs published in different countries or regions, which may suggest that the CPGs do not make sufficient use of the latest evidence. Conclusions Both the methodological and reporting qualities of COVID-19 CPGs increased over time, but there is still room for further improvement. The lack of effective use of available evidence and management of conflicts of interest were the main reasons for the low quality of the CPGs. The use of formal rating systems for the quality of evidence and strength of recommendations may help to improve the quality of CPGs in the context of the COVID-19 pandemic. During the pandemic, we suggest developing a living guideline of which recommendations are supported by a systematic review for it can facilitate the timely translation of the latest research findings to clinical practice. We also suggest that CPG developers should register the guidelines in a registration platform at the beginning for it can reduce duplication development of guidelines on the same clinical question, increase the transparency of the development process, and promote cooperation among guideline developers all over the world. Since the International Practice Guideline Registry Platform has been created, developers could register guidelines prospectively and internationally on this platform

Study of chattering suppression for the sliding mode controller of an electromagnetic levitation system

Due to the inherent non-linearity and open-loop instability of maglev systems, their high-quality control performance is critical in the development stage. Sliding mode control has great potential in the field of maglev vehicle control because of its superior control performance, robustness and interference resistance. In practical applications of sliding mode control, however, the limitations of the hardware physical properties and time delay of the control units of maglev systems can cause chattering, thereby significantly reducing the stability of maglev vehicles. In order to suppress chattering, a modified sliding mode controller that combines the exponential reaching law and continuous control laws is proposed in this study. A single-point levitation experimental platform and corresponding co-simulation model were built, and a parameter influence analysis of the modified sliding mode controller was conducted. This paper presents an adaptive correction method for the sliding mode control parameters based on the aforementioned chattering study. The actual levitation experiments were used to validate the control performance of the proposed controllers. Overall, the conducted research revealed that the modified controllers could effectively suppress chattering and possess excellent robustness

Study of chattering suppression for the sliding mode controller of an electromagnetic levitation system

Due to the inherent non-linearity and open-loop instability of maglev systems, their high-quality control performance is critical in the development stage. Sliding mode control has great potential in the field of maglev vehicle control because of its superior control performance, robustness and interference resistance. In practical applications of sliding mode control, however, the limitations of the hardware physical properties and time delay of the control units of maglev systems can cause chattering, thereby significantly reducing the stability of maglev vehicles. In order to suppress chattering, a modified sliding mode controller that combines the exponential reaching law and continuous control laws is proposed in this study. A single-point levitation experimental platform and corresponding co-simulation model were built, and a parameter influence analysis of the modified sliding mode controller was conducted. This paper presents an adaptive correction method for the sliding mode control parameters based on the aforementioned chattering study. The actual levitation experiments were used to validate the control performance of the proposed controllers. Overall, the conducted research revealed that the modified controllers could effectively suppress chattering and possess excellent robustness

Anti-GPIb/IX autoantibodies are associated with poor response to dexamethasone combined with rituximab therapy in primary immune thrombocytopenia patients

This retrospective study aimed to evaluate whether anti-glycoproteins (GPs) autoantibodies can be used as predictors of response to high-dose dexamethasone combined with rituximab (DXM-RTX) in the treatment of primary immune thrombocytopenia (ITP) patients. One-hundred twenty-six ITP patients were included and retrospectively analyzed, 66.7% of anti-GPIb/IX and 65.9% of anti-GPIIb/IIIa autoantibodies. Results showed that overall response (OR) and complete response (CR) rates of patients without anti-GPIb/IX autoantibodies to DXM-RTX were significantly higher than those with anti-GPIb/IX autoantibodies at 4 weeks (OR: 73.8% vs. 47.6%, CR: 50.0% vs. 26.2%; P < 0.05) and 6 months (OR: 71.4% vs. 45.2%, CR: 42.9% vs. 25.0%; P < .05). Furthermore, patients with anti-GPIb/IX single-positivity exhibited higher resistance to DXM-RTX than patients with anti-GPIIb/IIIa single-positivity at 4 weeks (OR: 37.5% vs. 78.3%; P < .05) and 6 months (OR: 29.2% vs. 78.3%; P < .05). Multivariable logistic regression analysis revealed that anti-GPIb/IX autoantibodies and megakaryocytes were associated with the OR rate of patients at both 4 weeks and 6 months, and anti-GPIb/IX autoantibodies at 4 weeks represented the only significant factor affecting OR rate with DXM-RTX (F = 9.128, P  = .003). Therefore, platelet anti-GPIb/IX autoantibodies might predict poor response to DXM-RTX in ITP patients

NAC Transcription Factor PwNAC11 Activates ERD1 by Interaction with ABF3 and DREB2A to Enhance Drought Tolerance in Transgenic Arabidopsis

NAC (NAM, ATAF1/2, and CUC2) transcription factors are ubiquitously distributed in eukaryotes and play significant roles in stress response. However, the functional verifications of NACs in Picea (P.) wilsonii remain largely uncharacterized. Here, we identified the NAC transcription factor PwNAC11 as a mediator of drought stress, which was significantly upregulated in P. wilsonii under drought and abscisic acid (ABA) treatments. Yeast two-hybrid assays showed that both the full length and C-terminal of PwNAC11 had transcriptional activation activity and PwNAC11 protein cannot form a homodimer by itself. Subcellular observation demonstrated that PwNAC11 protein was located in nucleus. The overexpression of PwNAC11 in Arabidopsis obviously improved the tolerance to drought stress but delayed flowering time under nonstress conditions. The steady-state level of antioxidant enzymes’ activities and light energy conversion efficiency were significantly increased in PwNAC11 transgenic lines under dehydration compared to wild plants. PwNAC11 transgenic lines showed hypersensitivity to ABA and PwNAC11 activated the expression of the downstream gene ERD1 by binding to ABA-responsive elements (ABREs) instead of drought-responsive elements (DREs). Genetic evidence demonstrated that PwNAC11 physically interacted with an ABA-induced protein—ABRE Binding Factor3 (ABF3)—and promoted the activation of ERD1 promoter, which implied an ABA-dependent signaling cascade controlled by PwNAC11. In addition, qRT-PCR and yeast assays showed that an ABA-independent gene—DREB2A—was also probably involved in PwNAC11-mediated drought stress response. Taken together, our results provide the evidence that PwNAC11 plays a dominant role in plants positively responding to early drought stress and ABF3 and DREB2A synergistically regulate the expression of ERD1