In silico approach to explore the mechanism of bioactive ingredients from Belamcandae rhizoma against COVID-19

Background:To date,the epidemic of COVID-19,which result from newly discovered virus named SARS-CoV-2,has spawned a heavy economic loss and continued to claim tens of thousands of lives.It’s urgent now that develop an ideal agent for suppressing the lifecycle of coronavirus while alleviate collateral severe inflammatory response.Belamcandae rhizoma,an herb which documented in various Chinese traditional medicine prescription,was reported to have effects of antiviral,anti-inflammatory and antipyretic.However,the relationship and related molecular mechanism between Belamcandae rhizoma and coronavirus are still unknown.Methods:Here,we achieved 14 kernel compounds from Belamcandae rhizoma and 261 validated“novel coronavirus pneumonia”correlative gene targets using a series of databases.Results:Subsequently,the pharmacology network and protein-protein interaction cluster,which constructed by the 20 overlapped genes targets between Belamcandae rhizoma and COVID-19,demonstrated that IL10,PTGS2,IL6,MAPK1,MAPK14 and CASP3 were as key targets in the treatment.The potential molecular mechanism involved IL-17,JAK-STAT and MAPK signaling pathways gained from gene enrichment analysis attract our attention.Molecular docking with 3CLpro of SARS-CoV-2 further suggested that luteolin and dinatin were the most bioactive compounds of Belamcandae rhizoma,among which luteolin connected with the maximum number of gene targets in above pharmacology network.Conclusion:Taken together,these findings provide deep insight into the putative therapeutic targets and underlying mechanism for COVID-19 treatment.

Application of distributed model predictive control based on neighborhood optimization in gauge-looper integrated system of tandem hot rolling

To solve the coupling relationship between the strip automatic gauge control and the looper control in traditional control strategy of tandem hot rolling,a distributed model predictive control(DMPC)strategy for the tandem hot rolling was explored,and a series of simulation experiments were carried out.Firstly,based on the state space analysis method,the multivariable dynamic transition process of hot strip rolling was studied,and the state space model of a gauge-looper integrated system in tandem hot rolling was established.Secondly,DMPC strategy based on neighborhood optimization was proposed,which fully considered the coupling relationship in this integrated system.Finally,a series of experiments simulating disturbances and emergency situations were completed with actual rolling data.The experimental results showed that the proposed DMPC control strategy had better performance compared with the traditional proportional-integral control and centralized model predictive control,which is applicable for the gauge-looper integrated system.

Lack of evolutionary convergence in multiple primary lung cancer suggests insufficient specificity of personalized therapy

Multiple primary lung cancer(MPLC)is an increasingly prevalent subtype of lung cancer.According to recent genomic studies,the different lesions of a single MPLC patient exhibit functional similarities that may reflect evolutionary convergence.We perform whole-exome sequencing for a unique cohort of MPLC patients with multiple samples from each lesion found.Using our own and other relevant public data,evolutionary tree reconstruction reveals that cancer driver gene mutations occurred at the early trunk,indicating evolutionary contingency rather than adaptive convergence.Additionally,tumors from the same MPLC patient are as genetically diverse as those from different patients,while within-tumor genetic heterogeneity is significantly lower.Furthermore,the aberrant molecular functions enriched in mutated genes for a sample show a strong overlap with other samples from the same tumor,but not with samples from other tumors or other patients.Overall,there is no evidence of adaptive convergence during the evolution of MPLC.Most importantly,the similar between-tumor diversity and between-patient diversity suggest that personalized therapies may not adequately account for the genetic diversity among different tumors in an MPLC patient.To fully exploit the strategic value of precision medicine,targeted therapies should be designed and delivered on a per-lesion basis.

基于数据挖掘和元模型的离心压缩机机匣多目标优化（英文）

Casing treatment(CT) has the potential to extend the stable operating range of a centrifugal compressor.A multi-objective optimization method is proposed to optimize the CT of centrifugal compressors. The method consists of Kriging metamodel, Genetic Algorithm(GA), data-mining techniques and CFD code. Firstly, data-mining techniques are used to analyze the initial design space. The correlations between design variables and objectives are extracted,resulting in a refined design space. Then, the global optimization of CT is conducted by GA based on data-mining results. After optimization, the performance of the centrifugal compressor shows a considerable improvement over the whole speed line. The isentropic efficiency increases by 2.05%, and the stall margin improves by 7.11%. Finally, the mechanism behind the performance improvement is further clarified by detailed flow analysis.

The Survival Analysis of a Non-autonomous N-dimensional Volterra Mutualistic System in a Polluted Environment

In this paper,we extend the autonomous n-Dimensional Volterra Mutualistic System to a non-autonomous system.The condition of persistence and extinction is obtained for each population,and thethreshold is established for asymptotically autonomous system.

Fault detection for sector-bounded non-linear systems with servo inputs and sensor stuck faults

This paper addresses the fault detection(FD)problem for discretetime sector-bounded non-linear systems with finite-frequency servo inputs.The non-linear systems are firstly modelled as multi-models.The main contributions are that a novel FD filter which combines the finite-frequency H∞and H−indices is designed.Different from the existing methods,the proposed FD scheme guarantees that the generated residuals are robust against the servo inputs in fault-free case and sensitive to them in faulty cases.Thus,the small sensor stuck faults including outagefaults can be detected.For this class of systems,the existing finite-frequency FD filter design methods are invalid.A new lemma is developed to characterise the system performances in finite-frequency domain.In addition,sufficient conditions for the existence of such a FD filter are derived by introducing slack variable and linear matrix inequalities techniques.Finally,an example is presented to demonstrate the method and its effectiveness.