Electric modulation of anisotropic magnetoresistance in Pt/HfO_(2-x)/NiO_(y)/Ni heterojunctions

Electric field control of magnetism through nanoionics has attracted tremendous attention owing to its high efficiency and low power consumption.In solid-state dielectrics,an electric field drives the redistribution of ions to create onedimensional magnetic conductive nanostructures,enabling the realization of intriguing magnetoresistance(MR)effects.Here,we explored the electric-controlled nickel and oxygen ion migration in Pt/HfO_(2-x)/NiO_(y)/Ni heterojunctions for MR modulation.By adjusting the voltage polarity and amplitude,the magnetic conductive filaments with mixed nickel and oxygen vacancy are constructed.This results in the reduction of device resistance by~10^(3)folds,and leads to an intriguing partial asymmetric MR effect.We show that the difference of the device resistance under positive and negative saturation magnetic fields exhibits good linear dependence on the magnetic field angle,which can be used for magnetic field direction detection.Our study suggests the potential of electrically controlled ion migration in creating novel magnetic nanostructures for sensor applications.

Noise-Filtering Enhanced Deep Cognitive Diagnosis Model for LatentSkill Discovering

Educational data mining based on student cognitive diagnosis analysis can provide an important decision basis for personalized learning tutoring of students,which has attracted extensive attention from scholars at home and abroad and has made a series of important research progress.To this end,we propose a noise-filtering enhanced deep cognitive diagno-sis method to improve the fitting ability of traditional models and obtain students’skill mastery status by mining the interaction between students and problems nonlinearly through neural networks.First,modeling complex interactions between students and problems with multidimensional features based on cognitive processing theory can enhance the interpretability of the proposed model;second,the neural network is used to predict students’learning performance,diagnose students’skill mastery and provide immediate feedback;finally,by comparing the proposed model with several baseline models,extensive experimental results on real data sets demonstrate that the proposed Finally,by comparing the proposed model with several baseline models,the extensive experimental results on the actual data set demon-strate that the proposed model not only improves the accuracy of predicting students’learning performance but also enhances the interpretability of the neurocognitive diagnostic model.

人工智能时代的教育测评通用理论框架与实践进路

人工智能技术的发展和深度应用为教育测评的智能化提供了技术支撑。本文结合国内外相关研究探讨教育测评理论的内涵、分类和应用场景,发现测评目标从宏观能力向微观知识转变、测评场景从单次静态向持续动态转变、测评方法从传统概率统计向深度学习转变。智能时代的教育测评需要以传统教育测量理论为指导,实现面向认知过程的时序动态建模分析。因此,本文提出人工智能时代教育测评模型通用性理论框架,包括教育数据分析、教育测评建模、模型参数估计、测评模型评估和创新教学应用等核心步骤,并通过经典模型的对比剖析智能化教育测评模型的内部运转规律。未来智能化测评研究的开展需要探索知识建构、认知发展和综合能力的理论价值,构建基于多维知识空间的认知诊断模型和面向时序数据的认知过程跟踪模型,并从智能化数据采集、智能化建模分析、教师数据素养等方面保证智能化教育测评的实施。

Ultra-robust stretchable electrode for e-skin:In situ assembly using a nanofiber scaffold and liquid metal to mimic water-to-net interaction

The development of stretchable electronics could enhance novel interface structures to solve the stretchability-conductivity dilemma,which remains a major challenge.Herein,we report a nano-liquid metal(LM)-based highly robust stretchable electrode(NHSE)with a self-adaptable interface that mimics water-tonet interaction.Based on the in situ assembly of electrospun elastic nanofiber scaffolds and electrosprayed LM nanoparticles,the NHSE exhibits an extremely low sheet resistance of 52 mΩsq^(-1).It is not only insensitive to a large degree of mechanical stretching(i.e.,350%electrical resistance change upon 570%elongation)but also immune to cyclic deformation(i.e.,5%electrical resistance increases after 330000 stretching cycles with 100%elongation).These key properties are far superior to those of the state-of-the-art reports.Its robustness and stability are verified under diverse circumstances,including long-term exposure to air(420 days),cyclic submersion(30000 times),and resilience against mechanical damages.The combination of conductivity,stretchability,and durability makes the NHSE a promising conductor/electrode solution for flexible/stretchable electronics for applications such as wearable on-body physiological signal detection,human-machine interaction,and heating e-skin.

Thickness-dependent and strain-tunable magnetism in twodimensional van der Waals VSe_(2)

Two-dimensional(2D)van der Waals(vdW)magnetic materials with reduced dimensionality often exhibit unexpected properties compared to their bulk counterparts.In particular,the mechanical flexibility of 2D structure,enhanced ferromagnetism at reduced layer thickness,as well as robust perpendicular magnetic anisotropy are quite appealing for constructing novel spintronic devices.The vdW vanadium diselenide(VSe_(2))is an attractive material whose bulk is paramagnetic while monolayer is ferromagnetic with a Curie temperature(Tc)above room temperature.To explore its possible device applications,a detailed investigation on the thickness-dependent magnetism and strain modulation behavior of VSe_(2)is highly demanded.In this article,the VSe_(2)nanoflakes were controllably prepared via chemical vapor deposition(CVD)method.The few-layer single VSe_(2)nanoflakes were found to exhibit magnetic domain structures at room temperature.Ambient magnetic force microscopy(MFM)phase images reveal a clear thickness-dependent magnetism and the MFM phase contrast is traceable for the nanoflakes of layer thickness below~6 nm.Moreover,applying strain is found efficient in modulating the magnetic moment and coercive field of 2D VSe_(2)at room temperature.These results are helpful for understanding the ferromagnetism of high temperature 2D magnets and for constructing novel straintronic devices or flexible spintronic devices.

PRICING FOR CORPORATE PROPERTY RIGHTS TRANSFER WITH STOCHASTIC MARKETS

This paper employs the real option theory to develop a pricing model for the transfer of property rights.We list the conditions for the good,intermediate and bad firms respectively,and work out the closed-form solution to the equilibrium transfer price,the optimal transfer timing.Using the comparative static analysis,we find that for good firms the transfer price of the target is increasing in its capital.The higher the capital of the target owns,the faster it will be transferred.For intermediate and bad firms,similar conclusions can be derived.The larger gap between the acquirer＇s size and market power and those of the target,the lower the transfer triggered price.The transfer price goes up as the capital ratio of the acquirer over the target diminishes,while it is decreasing in the amount of the capital the target owns.