Comparison of the Immunoregulatory Function of Different Constituents in Radix Astragali and Radix Hedysari

Radix Astragali (RA), known as “Huangqi” in China, is one of the most popular herbal medicines known worldwide to reinforce “Qi”. RA is traditionally prepared from the dried roots of Astragalus membranaceus (MJHQ) and A. membranaceus var. mongholicus (MGHQ). Radix Hedysari is named “Hongqi” (HQ), which is similar to RA. We assessed and compared the chemical constituents and bioactivity of RA and HQ. Different constituents were extracted into five major parts and were analyzed using different methods. Comparison of the immunological effects of extracts was done by using two immunological models. Results showed that flavonoids and saponins present in RA and HQ were not only structurally significantly different but also different in their immunological effect. Amino acids extract (AE) in MGHQ shows immunological effect while AE in MJHQ and HQ did not. Polysaccharides comprised the major constituents in RA and HQ. All polysaccharides extract (PE) of the three herbs showed similar levels of immunological effect in both immunological assays

ESMC: Entire Space Multi-Task Model for Post-Click Conversion Rate via Parameter Constraint

Large-scale online recommender system spreads all over the Internet being in charge of two basic tasks: Click-Through Rate (CTR) and Post-Click Conversion Rate (CVR) estimations. However, traditional CVR estimators suffer from well-known Sample Selection Bias and Data Sparsity issues. Entire space models were proposed to address the two issues via tracing the decision-making path of "exposure_click_purchase". Further, some researchers observed that there are purchase-related behaviors between click and purchase, which can better draw the user's decision-making intention and improve the recommendation performance. Thus, the decision-making path has been extended to "exposure_click_in-shop action_purchase" and can be modeled with conditional probability approach. Nevertheless, we observe that the chain rule of conditional probability does not always hold. We report Probability Space Confusion (PSC) issue and give a derivation of difference between ground-truth and estimation mathematically. We propose a novel Entire Space Multi-Task Model for Post-Click Conversion Rate via Parameter Constraint (ESMC) and two alternatives: Entire Space Multi-Task Model with Siamese Network (ESMS) and Entire Space Multi-Task Model in Global Domain (ESMG) to address the PSC issue. Specifically, we handle "exposure_click_in-shop action" and "in-shop action_purchase" separately in the light of characteristics of in-shop action. The first path is still treated with conditional probability while the second one is treated with parameter constraint strategy. Experiments on both offline and online environments in a large-scale recommendation system illustrate the superiority of our proposed methods over state-of-the-art models. The real-world datasets will be released

On methods for assessment of the influence and impact of observations in convection-permitting numerical weather prediction

In numerical weather prediction (NWP), a large number of observations are used to create initial conditions for weather forecasting through a process known as data assimilation. An assessment of the value of these observations for NWP can guide us in the design of future observation networks, help us to identify problems with the assimilation system, and allow us to assess changes to the assimilation system. However, the assessment can be challenging in convection-permitting NWP. First, the strong nonlinearity in the forecast model limits the methods available for the assessment. Second, convection-permitting NWP typically uses a limited area model and provides short forecasts, giving problems with verification and our ability to gather sufficient statistics. Third, convection-permitting NWP often makes use of novel observations, which can be difficult to simulate in an observing system simulation experiment (OSSE). We compare methods that can be used to assess the value of observations in convection-permitting NWP and discuss operational considerations when using these methods. We focus on their applicability to ensemble forecasting systems, as these systems are becoming increasingly dominant for convection-permitting NWP. We also identify several future research directions: comparison of forecast validation using analyses and observations, the effect of ensemble size on assessing the value of observations, flow-dependent covariance localization, and generation and validation of the nature run in an OSSE.Comment: 35 page

Spatial-temporal clustering of an outbreak of SARS-CoV-2 Delta VOC in Guangzhou, China in 2021

BackgroundIn May 2021, the SARS-CoV-2 Delta variant led to the first local outbreak in China in Guangzhou City. We explored the epidemiological characteristics and spatial-temporal clustering of this outbreak.MethodsBased on the 153 cases in the SARS-CoV-2 Delta variant outbreak, the Knox test was used to analyze the spatial-temporal clustering of the outbreak. We further explored the spatial-temporal clustering by gender and age groups, as well as compared the changes of clustering strength (S) value between the two outbreaks in Guangzhou.ResultsThe result of the Knox analysis showed that the areas at short distances and brief periods presented a relatively high risk. The strength of clustering of male-male pairs was higher. Age groups showed that clustering was concentrated in cases aged ≤ 18 years matched to 18–59 years and cases aged 60+ years. The strength of clustering of the outbreak declined after the implementation of public health measures. The change of strength of clustering at time intervals of 1–5 days decreased greater in 2021 (S = 129.19, change rate 38.87%) than that in 2020 (S = 83.81, change rate 30.02%).ConclusionsThe outbreak of SARS-CoV-2 Delta VOC in Guangzhou has obvious spatial-temporal clustering. The timely intervention measures are essential role to contain this outbreak of high transmission

Object Tracking Algorithm Based on Dual Color Feature Fusion with Dimension Reduction

Aiming at the problem of poor robustness and the low effectiveness of target tracking in complex scenes by using single color features, an object-tracking algorithm based on dual color feature fusion via dimension reduction is proposed, according to the Correlation Filter (CF)-based tracking framework. First, Color Name (CN) feature and Color Histogram (CH) feature extraction are respectively performed on the input image, and then the template and the candidate region are correlated by the CF-based methods, and the CH response and CN response of the target region are obtained, respectively. A self-adaptive feature fusion strategy is proposed to linearly fuse the CH response and the CN response to obtain a dual color feature response with global color distribution information and main color information. Finally, the position of the target is estimated, based on the fused response map, with the maximum of the fused response map corresponding to the estimated target position. The proposed method is based on fusion in the framework of the Staple algorithm, and dimension reduction by Principal Component Analysis (PCA) on the scale; the complexity of the algorithm is reduced, and the tracking performance is further improved. Experimental results on quantitative and qualitative evaluations on challenging benchmark sequences show that the proposed algorithm has better tracking accuracy and robustness than other state-of-the-art tracking algorithms in complex scenarios

Reactivity and Penetration Performance Ni-Al and Cu-Ni-Al Mixtures as Shaped Charge Liner Materials

Energetic structural materials (ESMs) have many potential military applications due to their unique functions. In this work, the reactivity and penetration performance of ESMs have been examined as a shaped charge liner material. The penetration experiments of nickel-aluminum (Ni-Al) and copper-nickel-aluminum (Cu-Ni-Al)-shaped charge liners (SCLs) have been designed and fired into 45# steel. The targets were recovered and analyzed by optical microscopy, electron microscopy, energy dispersive spectroscopy, and Vickers microhardness measurements. The head and tail of the crater walls penetrated by two reactive jets demonstrated unique microstructures. The jet rapidly decayed with the penetration process, but the “white„ zone (a mixture of martensite and austenite) was more prominent in the tail, and the microhardness of the tail was much higher than that of the head. The results showed the continued exotherm of Ni-Al reactive jet when it was fired into the target. The addition of Cu reduced the exotherm of Ni-Al, Cu could not only increase the average crater size, but also raise the average penetration depth by 42%. These results offer valuable insight for utilizing ESM as shaped charge liner materials