Noise-Tolerant ZNN-Based Data-Driven Iterative Learning Control for Discrete Nonaffine Nonlinear MIMO Repetitive Systems

Aiming at the tracking problem of a class of discrete nonaffine nonlinear multi-input multi-output(MIMO) repetitive systems subjected to separable and nonseparable disturbances, a novel data-driven iterative learning control(ILC) scheme based on the zeroing neural networks(ZNNs) is proposed. First, the equivalent dynamic linearization data model is obtained by means of dynamic linearization technology, which exists theoretically in the iteration domain. Then, the iterative extended state observer(IESO) is developed to estimate the disturbance and the coupling between systems, and the decoupled dynamic linearization model is obtained for the purpose of controller synthesis. To solve the zero-seeking tracking problem with inherent tolerance of noise,an ILC based on noise-tolerant modified ZNN is proposed. The strict assumptions imposed on the initialization conditions of each iteration in the existing ILC methods can be absolutely removed with our method. In addition, theoretical analysis indicates that the modified ZNN can converge to the exact solution of the zero-seeking tracking problem. Finally, a generalized example and an application-oriented example are presented to verify the effectiveness and superiority of the proposed process.

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.

Controllable assembling of highly-doped linked carbon bubbles on graphene microfolds

Carbon-based microassemblies(CMs) have attracted significant attention in numerous applications due to their unique hierarchical structures and delicate building blocks,especially when hollow carbon spheres(HCSs) are reasonably introduced into the construction.Herein,a new design for novel HCSscombined CMs is proposed.Remarkably,the HCSs are linear carbon bubbles linked one-by-one, arranging into necklaces decorating on the graphene microfolds.Detailed thermal analysis confirm that high temperatures straighten the linked carbon bubbles into bamboo-like carbon nanofibers,evidently due to the attenuation of doping degree.Benefiting from the abundant active sites of carbon bubbles,the obtained CMs exhibit satisfactory electrocatalytic activity for oxygen reduction reactions.This work establishes a bridge to precisely control the synthesis of carbon-based hierarchical architectures.

Generation of a scenario library for testing driver-automation cooperation safety under cut-in working conditions

To improve the efficiency of safety tests of driver-automation cooperation,a method for generating a scenario library is proposed that considers the probability of scenario occurrence and driver-handling challenges in real driving situations.First,the original scenario data under cut-in conditions stored in a time series are extracted from the scenario data set.Then,a mathematical performance index is used to model the scenario and a significance function in terms of the occurrence frequency of the scenario,and the performance challenge between the driver and the vehicle is established.Next,the important scenario set is extracted from the original scenario set by constructing and optimizing a significance auxiliary function.Finally,the extracted important scenario sets are filtered by using the significance function values of the scenarios to generate a scenario library.Simulation results show that the proposed method for scenario library generation can effectively identify scenarios with potential adventure during driver-automation cooperation and thus accelerate safety tests compared with traditional methods.

Nitric oxide synergizes minoxidil delivered by transdermal hyaluronic acid liposomes for multimodal androgenetic-alopecia therapy

Androgenetic alopecia(AGA)is a common clinical condition,affecting over 200 million people globally each year.For decades,Minoxidil(Mi)tincture has been the primary treatment for this disease,but its low utilization rate and significant side effects necessitate new therapeutic strategies.Nitric oxide(NO)is a signaling molecule in various physiological processes,including vasodilation,immune responses,and cell proliferation.Herein,we constructed a hyaluronic acid liposome(HL)complex as a novel transdermal delivery system(HL@Mi/NONOate)for NO and Mi,which displayed promising transdermal and hair-regrowth effects.In-depth mechanistic studies revealed three potential pathways of the synergistic AGA therapy.First,NO promoted capillary dilation and accelerated blood flow,thus achieving efficient penetration of Mi.Due to the structural advantage of liposomes,the residence time of the Mi in the skin was prolonged.Moreover,HL@Mi/NONOate promoted cell proliferation and angiogenesis,and upregulated the expression of regulatory factors involved in follicle stem cell differentiation.In the AGA model,HL@Mi/NONOate down-regulated the expression of inflammatory factors,inhibiting the inflammation of follicle and improving the microenvironment of hair regrowth.Concurrently,HL@Mi/NONOate upregulated the expression of Ki67 and PCNA proteins in follicle tissues,inducing follicle regeneration and development,ultimately achieving the synergistic multimodal AGA therapy.