Design Path of Ecological Learning Environment Based on Spatial Resilience

Nowadays,the city’s focus on education makes the improvement of learning environment become a new demand for development.From the the perspective of ecology,the theory of"resilience"is introduced to break the stereotype of the existing learning environment and create a space for dialogue with nature from inside to outside.At the same time,the learning environment is divided into observation learning space,exploration learning space and communication learning space by theory and method of multiple intelligence integrating teaching and learning.Through the analysis on resilience characteristics of three types of space,eight basic unit forms of learning environment design are obtained.Arrangement and combination of its form can improve the campus environment,increase children’s learning efficiency and the risk response ability of campus environment,and give children the opportunity to interact with and understand nature in the learning process,so as to provide reference for the diversified development of education and learning space.

The impact of the design of learning spaces on attention and memory from a neuroarchitectural approach:A systematic review

Enriched environments in animal models have demonstrated that exposure to an optimal stimulus improves behavior,cognition,and genomics.However,the evidence base for the neurophysiological influence of human environment enrichment has not been extensively studied.This systematic review compiles indicators about the effect of built,indoor environments on the cognitive processes of memory and attention in humans.This work pursues two main objectives:(1)to define current knowledge and the methods that are useful and identify whether previously published studies indicate consistencies and(2)to report the approaches and strategies that can be used in evaluating cognitive processes affected by environment response.Results of this systematic review show that(1)form and geometry,(2)space distribution and context,(3)color and texture,(4)height,width,and enclosure,(5)transition and circulation,and(6)light,sound,and temperature have an impact on memory and/or attention,and they can be assessed objectively.Despite all the advances in this field,methodological limitations and a lack of cross-validated standard protocols are found.Therefore,future research is necessary to provide a deep insight into how human cognition can be heightened by the environment to which it is exposed.

Tangent space learning and generalization

Manifold learning has attracted considerable attention over the last decade,in which exploring the geometry and topology of the manifold is the central problem.Tangent space is a fundamental tool in discovering the geometry of the manifold.In this paper,we will first review canonical manifold learning techniques and then discuss two fundamental problems in tangent space learning.One is how to estimate the tangent space from random samples,and the other is how to generalize tangent space to ambient space.Previous studies in tangent space learning have mainly focused on how to fit tangent space,and one has to solve a global equation for obtaining the tangent spaces.Unlike these approaches,we introduce a novel method,called persistent tangent space learning(PTSL),which estimates the tangent space at each local neighborhood while ensuring that the tangent spaces vary smoothly on the manifold.Tangent space can be viewed as a point on Grassmann manifold.Inspired from the statistics on Grassmann manifold,we use intrinsic sample total variance to measure the variation of estimated tangent spaces at a single point,and thus,the generalization problem can be solved by estimating the intrinsic sample mean on Grassmann manifold.We validate our methods by various experimental results both on synthetic and real data.

An enhanced eco-driving strategy based on reinforcement learning for connected electric vehicles:cooperative velocity and lane-changing control

Purpose–This study aims to propose an enhanced eco-driving strategy based on reinforcement learning(RL)to alleviate the mileage anxiety of electric vehicles(EVs)in the connected environment.Design/methodology/approach–In this paper,an enhanced eco-driving control strategy based on an advanced RL algorithm in hybrid action space(EEDC-HRL)is proposed for connected EVs.The EEDC-HRL simultaneously controls longitudinal velocity and lateral lane-changing maneuvers to achieve more potential eco-driving.Moreover,this study redesigns an all-purpose and efficient-training reward function with the aim to achieve energy-saving on the premise of ensuring other driving performance.Findings–To illustrate the performance for the EEDC-HRL,the controlled EV was trained and tested in various traffic flow states.The experimental results demonstrate that the proposed technique can effectively improve energy efficiency,without sacrificing travel efficiency,comfort,safety and lane-changing performance in different traffic flow states.Originality/value–In light of the aforementioned discussion,the contributions of this paper are two-fold.An enhanced eco-driving strategy based an advanced RL algorithm in hybrid action space(EEDC-HRL)is proposed to jointly optimize longitudinal velocity and lateral lane-changing for connected EVs.A full-scale reward function consisting of multiple sub-rewards with a safety control constraint is redesigned to achieve eco-driving while ensuring other driving performance.

Decrease of memory retention in a parasitic wasp： an effect of host manipulation by Wolbachia？

Several factors, such as cold exposure, aging, the number of experiences and viral infection, have been shown to affect learning ability in different organisms. Wol- bachia has been found worldwide as an arthropod parasite/mutualist symbiont in a wide range of species, including insects. Differing effects have been identified on physiology and behavior by Wolbachia. However, the effect of Wolbachia infection on the learning ability of their host had never previously been studied. The current study carried out to compare learning ability and memory duration in 2 strains of the parasitoid Trichogramma brassicae： 1 uninfected and I infected by Wolbachia. Both strains were able to associate the novel odors with the reward of an oviposition into a host egg. However, the percentage of females that responded to the experimental design and displayed an ability to learn in these conditions was higher in the uninfected strain. Memory duration was longer in uninfected wasps （23.8 and 21.4 h after conditioning with peppermint and lemon, respectively） than in infected wasps （18.9 and 16.2 h after conditioning with peppermint and lemon, respec- tively）. Memory retention increased in response to the number of conditioning sessions in both strains, but memory retention was always shorter in the infected wasps than in the uninfected ones. Wolbachia infection may select for reduced memory retention because shorter memory induces infected wasps to disperse in new environments and avoid compe- tition with uninfected wasps by forgetting cues related to previously visited environments, thus increasing transmission of Wolbachia in new environments.