Low-cost adaptive square-root cubature Kalman filter forsystems with process model uncertainty

A novel low-cost adaptive square-root cubature Kalmanfilter （LCASCKF） is proposed to enhance the robustness of processmodels while only increasing the computational load slightly.It is well-known that the Kalman filter cannot handle uncertainties ina process model, such as initial state estimation errors, parametermismatch and abrupt state changes. These uncertainties severelyaffect filter performance and may even provoke divergence. Astrong tracking filter （STF）, which utilizes a suboptimal fading factor,is an adaptive approach that is commonly adopted to solvethis problem. However, if the strong tracking SCKF （STSCKF）uses the same method as the extended Kalman filter （EKF） tointroduce the suboptimal fading factor, it greatly increases thecomputational load. To avoid this problem, a low-cost introductorymethod is proposed and a hypothesis testing theory is applied todetect uncertainties. The computational load analysis is performedby counting the total number of floating-point operations and it isfound that the computational load of LCASCKF is close to that ofSCKF. Experimental results prove that the LCASCKF performs aswell as STSCKF, while the increase in computational load is muchlower than STSCKF.

Consensus intuitionistic fuzzy group decision-making method for aircraft cockpit display and control system evaluation

A novel group decision-making （GDM） method based on intuitionistic fuzzy sets （IFSs） is developed to evaluate the ergonomics of aircraft cockpit display and control system （ACDCS）. The GDM process with four steps is discussed. Firstly, approaches are proposed to transform four types of common judgement representations into a unified expression by the form of the IFS, and the features of unifications are analyzed. Then, the aggregation operator called the IFSs weighted averaging （IFSWA） operator is taken to synthesize decision-makers’ （DMs’） preferences by the form of the IFS. In this operator, the DM’s reliability weights factors are determined based on the distance measure between their preferences. Finally, an improved score function is used to rank alternatives and to get the best one. An illustrative example proves the proposed method is effective to valuate the ergonomics of the ACDCS.

Highly Efficient Photothermocatalytic CO_(2) Reduction in Ni/Mg-Doped Al_(2)O_(3) with High Fuel Production Rate, Large Light-to-Fuel Efficiency, and Good Durability

A novel nanocomposite of Ni nanoparticles loaded on Mg-doped Al_(2)O_(3)(Ni/Mg-Al_(2)O_(3))was prepared.By photothermocatalytic CO_(2) reduction with methane(CRM)merely using focused UV-vis-IR illumination on Ni/Mg-Al_(2)O_(3),high production rates of H_(2)(r_(H2),69.71 mmol min^(−1) g^(−1))and CO(rCO,74.57 mmol min^(−1) g^(−1))and an extremely large light-to-fuel efficiency(η,32.9%)are acquired.High rH2 and rCO(51.07 and 59.66 mmol min^(−1) g^(−1))and a largeη(32.5%)are acquired even by using focusedλ>560 nm vis-IR illumination.Ni/Mg-Al_(2)O_(3) shows good durability for photothermocatalytic CRM due to the side reaction of carbon deposition being enormously inhibited in comparison with a reference catalyst of Ni nanoparticles loaded on Al_(2)O_(3).The enormous carbon deposition inhibition is ascribed to the presence of a fence of CO_(2) molecules(strongly adsorbed on Mg-doped Al_(2)O_(3))around Ni nanoparticles,which block the polymerization and growth of carbon species to nanofibers by promoting the oxidation of carbon species formed by CH_(4) dissociation.The high photothermocatalytic activity of Ni/Mg-Al_(2)O_(3) arises from efficient light-driven thermocatalytic CRM.A photoactivation is found to considerably raise the photothermocatalytic activity of Ni/Mg-Al_(2)O_(3) because of the apparent activation energy(Ea)being substantially decreased upon focused illumination.The Ea reduction is associated with the rate-determining steps of CRM(e.g.,CH_(4) dissociation and the oxidation of carbon species)being accelerated upon focused illumination.

Human-machine function allocation method for aircraft cockpit based on interval 2-tuple linguistic information

Appropriate human-machine function allocation benefits the complement between pilots and automation, and makes the whole system more effective and reliable. Thus, the humanmachine function allocation method for aircraft cockpit based on interval 2-tuple linguistic information is proposed. The uncertain expanded weighted arithmetic averaging (UEWAA) operator and uncertain linguistic hybrid aggregation (ULHA) operator are extended into the interval 2-tuple linguistic environment based on uncertain linguistic multiple attribute decision making (ULMADM). And some new aggregation operators are developed, including the interval 2-tuple weighted average aggregation (IT-WAA) operator and the interval 2-tuple weighted hybrid aggregation (IT-WHA) operator. Uniformization of the multiple-granularity linguistic evaluation information is introduced to solve the problem of ULMADM not being able to deal with the multiple-granularity linguistic information from different decision-makers. Then the detailed steps of the proposed method are described. Finally, an illustrative example of the ground proximity warning system (GPWS) is provided to demonstrate the practicality, feasibility and superiority based on the comparison between the proposed method and ULMADM. © 2016 Beijing Institute of Aerospace Information.

Obesity intervention efforts in China and the 2022 World Obesity Day

Obesity has become a serious public health problem globally.China has the world’s largest number of people with obesity or overweight.More than 50%of adults and about 20%of children and adolescents in China are overweight or obese.Over the past 20 years,China has made many efforts in obesity intervention,while obesity rates continued rising.In recent years,China has taken more actions for obesity prevention.The World Obesity Day(WOD)was established in 2015 by the World Obesity Federation,and is a unified day of action calling for a cohesive,cross-sector response to fight obesity.WOD has drawn increasing attention in recent years.China formally joined the WOD activities this year,promoted by The Obesity Prevention and Control Section of Chinese Nutrition Society,which cooperated closely with other organizations in carrying out a series of activities during the 2022 WOD.These efforts aimed to encourage the whole society to pay attention to the obesity problem and take more practical actions.The activities include:(1)The 2022“World Obesity Day”China Summit;(2)a specifically developed WOD obesity prevention education video;and(3)the launch of The Expert Consensus on Obesity Prevention and Treatment in China.These can serve as examples for other organizations and countries to consider in future intervention efforts.To fight the global obesity epidemic,all counties and people need to act.Countries can learn from each other’s successful practices.

Service allocation based on QoS evaluation in military organization cloud cooperation

The problem of cloud cooperation of military service providers（MSPs） is addressed for allocating limited resources to military service users（MSUs） that are geographically distributed. The MSPs, also called military organization clouds, are virtualized and encapsulated by the services they can offer and each of them contains different kinds of resources that MSU needs. The MSPs are also geographically dispersed. They are required to allocate their resources to the MSU complying with the corresponding quality of service（QoS）, so that each MSU gathers the services it needs to guarantee its task to be implemented. The outline of military organization cloud cooperation is discussed and the method of service optimal selection is proposed based on QoS evaluation. The QoS evaluation method based on exponential approximation is put forward to include the users＇ will. Simulation results verify the effectiveness of the proposed algorithm.

Service composition based on discrete particle swarm optimization in military organization cloud cooperation

This paper addresses the problem of service composition in military organization cloud cooperation（MOCC）. Military service providers（MSP） cooperate together to provide military resources for military service users（MSU）. A group of atom services, each of which has its level of quality of service（QoS）, can be combined together into a certain structure to form a composite service. Since there are a large number of atom services having the same function, the atom service is selected to participate in the composite service so as to fulfill users＇ will. In this paper a method based on discrete particle swarm optimization（DPSO） is proposed to tackle this problem. The method aims at selecting atom services from service repositories to constitute the composite service, satisfying the MSU＇s requirement on QoS. Since the QoS criteria include location-aware criteria and location-independent criteria, this method aims to get the composite service with the highest location-aware criteria and the best-match location-independent criteria. Simulations show that the DPSO has a better performance compared with the standard particle swarm optimization（PSO） and genetic algorithm（GA）.

Artificial intelligence:A new budding star in gastric cancer

The pursuit of health has always been the driving force for the advancement of human society,and social development will be profoundly affected by every breakthrough in the medical industry.With the arrival of the information technology revolution era,artificial intelligence(AI)technology has been rapidly developed.AI has been combined with medicine but it has been less studied with gastric cancer(GC).AI is a new budding star in GC,and its contribution to GC is mainly focused on diagnosis and treatment.For early GC,AI’s impact is not only reflected in its high accuracy but also its ability to quickly train primary doctors,improve the diagnosis rate of early GC,and reduce missed cases.At the same time,it will also reduce the possibility of missed diagnosis of advanced GC in cardia.Furthermore,it is used to assist imaging doctors to determine the location of lymph nodes and,more importantly,it can more effectively judge the lymph node metastasis of GC,which is conducive to the prognosis of patients.In surgical treatment of GC,it also has great potential.Robotic surgery is the latest technology in GC surgery.It is a bright star for minimally invasive treatment of GC,and together with laparoscopic surgery,it has become a common treatment for GC.Through machine learning,robotic systems can reduce operator errors and trauma of patients,and can predict the prognosis of GC patients.Throughout the centuries of development of surgery,the history gradually changes from traumatic to minimally invasive.In the future,AI will help GC patients reduce surgical trauma and further improve the efficiency of minimally invasive treatment of GC.

Resequencing of sweetpotato germplasm resources reveals key loci associated with multiple agronomic traits

Sweetpotato is an important crop that exhibits hexaploidy and high heterozygosity,which limits gene mining for important agronomic traits.Here,314 sweetpotato germplasm resources were deeply resequenced,and 4599509 SNPs and 846654 InDels were generated,among which 196124 SNPs were nonsynonymous and 9690 InDels were frameshifted.Based on the Indels,genome-wide marker primers were designed,and 3219 of 40366 primer pairs were selected to construct the core InDel marker set.The molecular ID of 104 sweetpotato samples verified the availability of these primers.The sweetpotato population structures were then assessed through multiple approaches using SNPs,and diverse approaches demonstrated that population stratification was not obvious for most Chinese germplasm resources.As many as 20 important agronomic traits were evaluated,and a genome-wide association study was conducted on these traits.A total of 19 high-confidence loci were detected in both models.These loci included several candidate genes,such as IbMYB1,IbZEP1,and IbYABBY1,which might be involved in anthocyanin metabolism,carotenoid metabolism,and leaf morphogenesis,respectively.Among them,IbZEP1 and IbYABBY1 were first reported in sweetpotato.The variants in the promoter and the expression levels of IbZEP1 were significantly correlated with f lesh color(orange or not orange)in sweetpotato.The expression levels of IbYABBY1 were also correlated with leaf shape.These results will assist in genetic and breeding studies in sweetpotato.

Clarification of the dispersion mechanism of cathode slurry of lithium-ion battery under effects of both poly vinylidene fluoride/carbon black ratio and mixing time

This paper presents the effects of both poly vinylidene fluoride(PVDF)/carbon black(CB)ratio(m PVDF:m CB)and mixing time t on the dispersion mechanism of the cathode slurry of lithium-ion battery(LIB).The dispersion mechanism is deduced from the electrochemical,morphological and rheological properties of the cathode slurry by using electrical impedance spectroscopy(EIS),scanning electron microscopy and rheology methods,respectively.From the perspective of EIS method,static simulation models are established in the COMSOL Multiphysics software;meanwhile,the simulated results are used to verify the correctness of the electrochemical properties of the cathode slurry.As a result,the following conclusions are able to be obtained.Firstly,in the case of the mass ratio m_(PVDF):m_(CB)=5:10,LiCoO_(2) particles are completely coated by the mixture of CB and PVDF to form a stable polymer gel structure.Higher or lower m_(PVDF):m_(CB) leads to the larger impedance and worse dispersion status for the cathode slurry.Secondly,when t=6 min,a good gel-like conductive network structure is formed by coating the thinner evenly dispersed CB–PVDF double layer around LiCoO_(2) particles.Finally,a strategy regarding to both m_(PVDF):m_(CB) and t in experimental scale is proposed,which has the capability of improving the performance of LIB.

Weld Defects in Laser-Welded 7A52 High-Strength Aluminum Alloy Plates with Varying Thicknesses

This study aims to explore a method suitable for welding 7A52 high-strength aluminum alloy plates with continuously varying thicknesses and the causes of microscopic defects in welds in order to improve welding quality.Comparative tests were conducted to analyze weld defects and deformation when welding the aluminum alloy plates with varying thicknesses at constant laser power.The laser power required for melting welds at varying-thickness positions was estimated.Weld defects and deformation when welding aluminum alloy plates with varying thicknesses at con-tinuous variable laser power were detected.The causes of microscopic weld defects during constant-power welding were analyzed.The welding defects and deformation and the welding quality were improved by welding aluminum alloy plates at continuous variable power.

Doubled Hecke Algebras and Related Quantum Schur Duality

We introduce the doubled Hecke algebra,which is an infinite-dimensional algebra generated by two Hecke algebras.This concept originates from the degenerate doubled Hecke algebra in the theory of Schur-Weyl duality related to enhanced reductive algebraic groups.We study the finite-dimensional natural representation of the doubled Hecke algebra on tensor space and prove that the doubled Hecke algebra forms a duality with the quantum group of Levi type.

甲基转移酶样蛋白家族的分子作用机制及在胃癌中的研究进展

甲基转移酶样蛋白(methyltransferase-like proteins,METTL)是一个大蛋白家族的一部分,其特征是存在s-腺苷甲硫氨酸(s-adenosylmethionine,SAM)的结合域,SAM是甲基化反应的共同底物.尽管这个蛋白家族的成员被显示或预测为RNA、DNA或蛋白质的甲基转移酶,但大多数甲基转移酶的特征仍然很差,识别这些潜在酶起作用的复合物有助于了解它们的功能和底物特异性.METTL蛋白家族与胃癌(gastric cancer,GC)的发生发展有密切作用,明确其与GC的关系与GC的诊断治疗及预后有着十分重要的作用.本研究是对METTL蛋白家族的作用机制及与GC的关系一次系统和全面的综述,以期为进一步研究这些潜在的新型甲基转移酶和GC的诊治提供重要的资源.

Combination method of conflict evidences based on evidence similarity

Aiming at the problem that the traditional Dempster Shafer (D-S) evidence theory cannot deal with conflicted evidences effectively and correctly, this paper points out that the key issue of this problem is to measure the degree of conflict between evidences correctly after analyzing various improved methods. The existing evidence conflict measure methods are analyzed, and a new evidence conflict measure method called evidence similarity measure based on the Tanimoto measure is proposed, while a new evidence combination method is proposed on the basis of evidence similarity measure. Firstly, the conflict degrees between evidences are obtained through the evidence similarity measure. Then the evidence sources are modified based on the credibility of different evidences and the weights of conflicted parts of evidences on different focal elements are determined. Finally, the fusion result is obtained by this method. Numerical examples show that the proposed method can effectively fuse evidences when evidences are consistent or highly conflicted, and it has a fast convergence speed, a high degree of accuracy and good adaptability.

COVID-19: Challenges to GIS with Big Data

The outbreak of the 2019 novel coronavirus disease(COVID-19)has caused more than 100,000 people infected and thousands of deaths.Currently,the number of infections and deaths is still increasing rapidly.COVID-19 seriously threatens human health,production,life,social functioning and international relations.In the fight against COVID-19,Geographic Information Systems(GIS)and big data technologies have played an important role in many aspects,including the rapid aggregation of multi-source big data,rapid visualization of epidemic information,spatial tracking of confirmed cases,prediction of regional transmission,spatial segmentation of the epidemic risk and prevention level,balancing and management of the supply and demand of material resources,and socialemotional guidance and panic elimination,which provided solid spatial information support for decision-making,measures formulation,and effectiveness assessment of COVID-19 prevention and control.GIS has developed and matured relatively quickly and has a complete technological route for data preparation,platform construction,model construction,and map production.However,for the struggle against the widespread epidemic,the main challenge is finding strategies to adjust traditional technical methods and improve speed and accuracy of information provision for social management.At the data level,in the era of big data,data no longer come mainly from the government but are gathered from more diverse enterprises.As a result,the use of GIS faces difficulties in data acquisition and the integration of heterogeneous data,which requires governments,businesses,and academic institutions to jointly promote the formulation of relevant policies.At the technical level,spatial analysis methods for big data are in the ascendancy.Currently and for a long time in the future,the development of GIS should be strengthened to form a data-driven system for rapid knowledge acquisition,which signifies ts that GIS should be used to reinforce the social operation parameterization of models and methods,especially when providing support for social management.

Effectiveness of adjunctive corticosteroid therapy in patients with severe COVID-19:A retrospective cohort study

BACKGROUND The effectiveness of adjunctive corticosteroid use in patients with coronavirus disease 2019(COVID-19)remains inconclusive.AIM To investigate the effectiveness of adjunctive corticosteroid therapy in patients with severe COVID-19.METHODS We conducted a retrospective analysis of the difference in several outcomes between patients with severe COVID-19 who received corticosteroid therapy(the corticosteroid group)and patients with severe COVID-19 who did not receive corticosteroid therapy(the non-corticosteroid group).RESULTS Seventy-five patients were included in this study.Of these,47 patients were in the corticosteroid group and 28 patients were in the non-corticosteroid group.There were no differences between the two groups in the total length of hospital stay,the length of intensive care unit stay,high-flow oxygen days,non-invasive ventilator days,invasive ventilation days,and mortality rate.Total lesion volume ratio,consolidation volume ratio and ground-glass opacity volume ratio in the corticosteroid group decreased significantly on day 14,while those in the noncorticosteroid group did not show a significant decrease.CONCLUSION Our results show that adjunctive corticosteroid use did not significantly improveclinical outcomes in severe COVID-19 patients,but might promote the absorptionof pulmonary lesions.Larger multicenter randomized controlled studies may beneeded to confirm this.

Synthesis of amorphous Pd-based nanocatalysts for efficient alcoholysis of styrene oxide and electrochemical hydrogen evolution

Amorphous nanomaterials with long-range disordered structures could possess distinct properties and promising applications,especially in catalysis,as compared with their conventional crystalline counterparts.It is imperative to achieve the controlled preparation of amorphous noble metal-based nanomaterials for the exploration of their phase-dependent applications.Here,we report a facile wet-chemical reduction strategy to synthesize various amorphous multimetallic Pd-based nanomaterials,including PdRu,PdRh,and PdRuRh.The phase-dependent catalytic performances of distinct Pd-based nanomaterials towards diverse catalytic applications have been demonstrated.Specifically,the usage of PdRu nanocatalysts with amorphous and crystalline face-centered cubic(fcc)phases can efficiently switch the ring-opening route of styrene oxide to obtain different products with high selectivity through alcoholysis reaction and hydrogenation reaction,respectively.Moreover,when used as an electrocatalyst for hydrogen evolution reaction(HER),the synthesized amorphous PdRh nanocatalyst exhibits low overpotential and high turnover frequency values,outperforming its crystalline fcc counterpart and most of the reported Pd-based HER electrocatalysts.

Predictors and dynamic online nomogram for postoperative delayed hyponatremia after endoscopic transsphenoidal surgery for pituitary adenomas:a single-center,retrospective,observational cohort study with external validation

Background Postoperative delayed hyponatremia(PDH)is a major cause of readmission after endoscopic transsphenoidal surgery(eTSS)for pituitary adenomas(PAs).However,the risk factors associated with PDH have not been well established,and the development of a dynamic online nomogram for predicting PDH is yet to be realized.We aimed to investigate the predictive factors for PDH and construct a dynamic online nomogram to aid in its prediction.Methods We analyzed the data of 226 consecutive patients who underwent eTSS for PAs at the Department of Neurosurgery in Jinling Hospital between January 2018 and October 2020.An additional 97 external patients were included for external validation.PDH was defined as a serum sodium level below 137 mmol/L,occurring on the third postoperative day(POD)or later.Results Hyponatremia on POD 1-2(OR=2.64,P=0.033),prothrombin time(PT)(OR=1.78,P=0.008),and percentage of monocytes(OR=1.22,P=0.047)were identified as predictive factors for PDH via multivariable logistic regression analysis.Based on these predictors,a nomogram was constructed with great discrimination in internal validation(adjusted AUC:0.613-0.688)and external validation(AUC:0.594-0.617).Furthermore,the nomogram demonstrated good performance in calibration plot,Brier Score,and decision curve analysis.Subgroup analysis revealed robust predictive performance in patients with various clinical subtypes and mild to moderate PDH.Conclusions Preoperative PT and the percentage of monocytes were,for the first time,identified as predictive factors for PDH.The dynamic nomogram proved to be a valuable tool for predicting PDH after eTSS for PAs and demonstrated good generalizability.Patients could benefit from early identification of PDH and optimized treatment decisions.

A novel strong tracking cubature Kalman filter and its application in maneuvering target tracking

The fading factor exerts a significant role in the strong tracking idea. However, traditional fading factor introduction method hinders the accuracy and robustness advantages of current strong-tracking-based nonlinear filtering algorithms such as Cubature Kalman Filter(CKF) since traditional fading factor introduction method only considers the first-order Taylor expansion. To this end, a new fading factor idea is suggested and introduced into the strong tracking CKF method.The new fading factor introduction method expanded the number of fading factors from one to two with reselected introduction positions. The relationship between the two fading factors as well as the general calculation method can be derived based on Taylor expansion. Obvious superiority of the newly suggested fading factor introduction method is demonstrated according to different nonlinearity of the measurement function. Equivalent calculation method can also be established while applied to CKF. Theoretical analysis shows that the strong tracking CKF can extract the thirdorder term information from the residual and thus realize second-order accuracy. After optimizing the strong tracking algorithm process, a Fast Strong Tracking CKF(FSTCKF) is finally established. Two simulation examples show that the novel FSTCKF improves the robustness of traditional CKF while minimizing the algorithm time complexity under various conditions.

Efficiency of community health service in urban and suburban areas of Shanghai:based on production function

Objective:To analyze the efficiency of community health service in urban and suburban areas of Shanghai.Methods:Fifty community health centers in Shanghai that registered to create“National Demonstration Community Health Center”in 2013 were included in our study.The service efficiency was analyzed with the methods of econometrics based on Cobb-Douglas production function.Results:Two production functions were formulated for urban community health services and those in suburban areas;the equation for urban areas was:lnY=7.778+0.450lnL+0.350lnK+μ;and the equation for suburban areas was:lnY=6.329+0.728lnL+0.350lnK+μ.The results showed that among the inputs,labor had more effect on output than capital did.It also showed that marginal ben-efit of labor was different in urban and suburban areas.Urban community health centers were in the interval of decreasing returns to scale,while suburban community health centers were in the interval of constant returns to scale.Conclusion:Increasing human resource investment is a key factor for increasing community health service output.Due to the difference of scale merit between urban and rural areas,govern-ment or other policy makers should make the development policy for them accordingly.Those com-munity health centers in urban areas should pay more attention to the service efficiency and service innovation.