A label noise filtering and label missing supplement framework based on game theory

Labeled data is widely used in various classification tasks.However,there is a huge challenge that labels are often added artificially.Wrong labels added by malicious users will affect the training effect of the model.The unreliability of labeled data has hindered the research.In order to solve the above problems,we propose a framework of Label Noise Filtering and Missing Label Supplement(LNFS).And we take location labels in Location-Based Social Networks(LBSN)as an example to implement our framework.For the problem of label noise filtering,we first use FastText to transform the restaurant's labels into vectors,and then based on the assumption that the label most similar to all other labels in the location is most representative.We use cosine similarity to judge and select the most representative label.For the problem of label missing,we use simple common word similarity to judge the similarity of users'comments,and then use the label of the similar restaurant to supplement the missing labels.To optimize the performance of the model,we introduce game theory into our model to simulate the game between the malicious users and the model to improve the reliability of the model.Finally,a case study is given to illustrate the effectiveness and reliability of LNFS.

Registration Based on ORB and FREAK Features for Augmented Reality Systems

This paper proposes a novel registration method for augmented reality(AR) systems based on Oriented FAST and RotatedBRIEF(ORB) and Fast Retina Keypoint(FREAK) natural features. In the proposed ORBFREAK method, feature extraction is implemented based on the combination of ORB and FREAK, and the feature points are matched using Hamming distance. To get good matching points, cross-checks and least median squares are used to perform outlier filtration, and camera pose is estimated using the matched points. Finally, AR is rendered.Experiments show that the proposed method improves the speed of registration to be in real time; the proposed method can accurately register the target object under the circumstances of partial occlusion of the object; and it also can overcome the effects of rotation, scale change, ambient light and distance.

A Blockchain-Based Authentication Protocol for WLAN Mesh Security Access

In order to deploy a secure WLAN mesh network,authentication of both users and APs is needed,and a secure authentication mechanism should be employed.However,some additional configurations of trusted third party agencies are still needed on-site to deploy a secure authentication system.This paper proposes a new block chain-based authentication protocol for WLAN mesh security access,to reduce the deployment costs and resolve the issues of requiring key delivery and central server during IEEE 802.11X authentication.This method takes the user’s authentication request as a transaction,considers all the authentication records in the mesh network as the public ledger and realizes the effective monitoring of the malicious attack.Finally,this paper analyzes the security of the protocol in detail,and proves that the new method can solve the dependence of the authentication node on PKI and CA.

Polymer-based hybrid materials and their application in personal health

With unprecedented properties and functions,polymer-based hybrid materials hold extremely important position in many fields.Here in this review,we summarized applications of polymer-based hybrid materials toward personal health.Firstly,theoretical calculation and in-situ visualization used to explore the interfacial interaction and formation of hybrid materials are introduced.Secondly,applications of polymer-based hybrid materials in personal health from proactive protection(anti-bacteria and harmful gas removal),health condition monitoring(breathing and sleep)to disease diagnosis(magnetic resonance imaging),and tissue therapy(dental restoration)are discussed.Additionally,aggregation-induced emission(AIE)organic molecules based optical sensors for personal security and polymer semiconductor for organic thin film transistors are simply discussed.Finally,we present the future tendency for preparing polymer-based hybrid materials that related with personal health.

Downscaling inversion of GRACE-derived groundwater storage changes based on ensemble learning

Gravity Recovery and Climate Experiment(GRACE)satellite data monitors changes in terrestrial water storage,including groundwater,at a regional scale.However,the coarse spatial resolution limits its applicability to small watershed areas.This study introduces a novel ensemble learning-based model using meteorological and topographical data to enhance spatial resolution.The effectiveness was evaluated using groundwater-level observation data from the Henan rainstorm-affected area in July 2021.The factors influencing Groundwater Storage Anomalies(GWSA)were explored using Permutation Importance(Pi)and other methods.The results demonstrate that feature engineering and Blender ensemble learning improve downscaling accuracy;the Root Mean Square Error(RMSE)can be reduced by up to 18.95%.Furthermore,Blender ensemble learning decreased the RMSE by 3.58%,achieving an R-Square(R3)value of 0.7924.Restricting the downscaling inversion to June-August data greatly enhanced the accuracy,as evidenced by a holdout dataset test with an R2 value of 0.8247.The overall GWSA variation from January to August exhibited'slow rise,slow fall,sharp fall,and sharp rise.Additionally,heavy rain exhibits a lag effect on the groundwater supply.Meteorological and topographical factors drive fluctuations in GwSA values and changes in spatial distribution.Human activities also have a significant impact.

Spider web-like carbonized bacterial cellulose/MoSe_(2) nanocomposite with enhanced microwave attenuation performance and tunable absorption bands

It is essential to manufacture microwave absorbers with strong absorption as well as tunable absorption bands at a low filler content.However,it remains challenging for pure biomass material to reach this goal without loading other components.MoSe_(2),as a transition metal chalcogenide with semiconductor properties,has emerged as a potential microwave absorber filler.Herein,bacterial cellulose(BC)-derived carbon nanofibers/MoSe_(2) nanocomposite was fabricated and phosphoric acid was used to dope phosphorus in BC,in which MoSe_(2) microspheres were dropped on the BC network like a dew-covered spider web.This unique network structure enhances conductive loss and multiple reflections of the incident wave.The collocation of BC and MoSe_(2) is helpful to impedance match and introduces interfacial/dipolar polarization loss;moreover,the P-doping of BC helps to tune the absorption bands.Overall,the optimal reflection loss of undoped one reaches−53.33 dB with only 20 wt.%filler content,whose main absorption peaks focus on X-band.Interestingly,after the P-doping of BC,the main absorption peaks move to Ku-band and the optimal reflection loss gets stronger(−66.84 dB)with the same filler loading.Strong absorption and tunable absorption bands can be realized,and thus wide frequency range is covered.This work is expected to enlighten future exploration of biomass carbon materials on high-performance microwave absorption materials.

A baicalin-loaded coaxial nanofiber scaffold regulated inflammation and osteoclast differentiation for vascularized bone regeneration

We demonstrate a simple,effective and feasible method to address the shrinkage of Poly(lactic-co-glycolic acid)(PLGA)through a core-shell structure fiber strategy.The results revealed that introducing size-stable poly-caprolactone(PCL)as the core fiber significantly improved the PLGA-based fibrous scaffold’s dimensional maintenance.We further utilized fish collagen to modify the PLGA shell layer(PFC)of coaxial fibers and loaded baicalin(BA)into the PCL core layer(PCL-BA)to endow fibrous scaffold with more functional biological cues.The PFC/PCL-BA fibrous scaffold promoted the osteogenic differentiation of bone mesenchymal stem cells and stimulated the RAW264.7 cells to polarize into a pro-reparative phenotype.Importantly,the in vivo study demonstrated that the PFC/PCL-BA scaffold could regulate inflammation and osteoclast differentiation,favor neovascularization and bone formation.This work tactfully combined PLGA and PCL to establish a drug release platform based on the core-shell fibrous scaffold for vascularized bone regeneration.

The Application of UAV-Based Hyperspectral Imaging to Estimate Crop Traits in Maize Inbred Lines

Crop traits such as aboveground biomass(AGB),total leaf area(TLA),leaf chlorophyll content(LCC),and thousand kernel weight(TWK)are important indices in maize breeding.How to extract multiple crop traits at the same time is helpful to improve the efficiency of breeding.Compared with digital and multispectral images,the advantages of high spatial and spectral resolution of hyperspectral images derived from unmanned aerial vehicle(UAV)are expected to accurately estimate the similar traits among breeding materials.This study is aimed at exploring the feasibility of estimating AGB,TLA,SPAD value,and TWK using UAV hyperspectral images and at determining the optimal models for facilitating the process of selecting advanced varieties.The successive projection algorithm(SPA)and competitive adaptive reweighted sampling(CARS)were used to screen sensitive bands for the maize traits.Partial least squares(PLS)and random forest(RF)algorithms were used to estimate the maize traits.The results can be summarized as follows:The sensitive bands for various traits were mainly concentrated in the near-red and red-edge regions.The sensitive bands screened by CARS were more abundant than those screened by SPA.For AGB,TLA,and SPAD value,the optimal combination was the CARS-PLS method.Regarding the TWK,the optimal combination was the CARS-RF method.Compared with the model built by RF,the model built by PLS was more stable.This study provides guiding significance and practical value for main trait estimation of maize inbred lines by UAV hyperspectral images at the plot level.

ALTERING CONNECTIVITY WITH LARGE DEFORMATION MESH FOR LAGRANGIAN METHOD AND ITS APPLICATION IN MULTIPLE MATERIAL SIMULATION

A new approach for treating the mesh with Lagrangian scheme of finite volume method is presented. It has been proved that classical Lagrangian method is difficult to cope with large deformation in tracking material particles due to severe distortion of cells, and the changing connectivity of the mesh seems especially attractive for solving such issues. The mesh with large deformation based on computational geometry is optimized by using new method. This paper develops a processing system for arbitrary polygonal unstructured grid,the intelligent variable grid neighborhood technologies is utilized to improve the quality of mesh in calculation process, and arbitrary polygonal mesh is used in the Lagrangian finite volume scheme. The performance of the new method is demonstrated through series of numerical examples, and the simulation capability is efficiently presented in coping with the systems with large deformations.

Asymmetric polymerase chain reaction and loop-mediated isothermal amplification(AP-LAMP) for ultrasensitive detection of microRNAs

In this manuscript,we first report an ultrasensitive detection assay of microRNA by combing asymmetric polymerase chain reaction(A-PCR)and loop-mediated isothermal amplification(LAMP)technology.Using A-PCR obtained an extended single strand to form LAMP stem-loop structure under isothermal amplification conditions.We used miRNAs as a loop primer probe in LAMP reaction and completed its ultrasensitive and rapid detection.The established method furnished a fast,specific and efficient detection of target miRNA with a detection limit as low as 10 amol/L in 90 min.

Selective recognition of HIV RNA by dinuclear metallic ligands

We describe the development of dinuclear metallic ligands to target specific HIV RNA structures. Two series of dipyridinyl-N bridged dinuclear metal complexes were synthesized in moderate to good yields and their binding activities toward TAR and RRE RNA were studied both experimentally and theoretically. The docking calculation elucidated some structure features in dimetallic complexes that can affect TAR RNA-binding properties.