A Case Study of Educational Equity in Saskatchewan Schools and Implications for Educational Development in China

This paper probes the phenomenon of underperforming indigenous students in Canada through a case study in the school district of Saskatchewan. It is discerned that the disparity between indigenous students’ home culture and the mainstream classroom culture is the major obstacle between indigenous students and academic success. Such a disparity is caused by a couple of reasons. First of all, educators’ misconception, along with education decision-makers’ ineffectiveness, leads to adversity for indigenous students to face in the classroom; secondly, biased evaluation and misjudgments in the current education system also result in indigenous students’ underperformance. Lastly, educators’ low cultural proficiency towards indigenous culture culminates in indigenous students’ low classroom engagement. The results of the case study could be enlightening for Chinese education decision-makers, given that the Chinese booming economy has caused millions of internal migrant workers to work in an alien subculture, their children could face similar social and linguistic debacles as compared to indigenous students in Saskatchewan

“Somewhere I belong?” A study on transnational identity shifts caused by “double stigmatization” among Chinese international student returnees during COVID-19 through the lens of mindsponge mechanism

Chinese international students who studied in the United States received “double stigmatization” from American and Chinese authorities because of the “political othering” tactic during COVID-19. The research used a phenomenological approach to examine why and how specifically the transnational identity of Chinese international students in the United States shifted during the double stigmatization. The researcher conducted a total of three rounds of interviews with 15 Chinese international students who studied in the United States and returned to China between 2018 and 2020, which culminated in 45 interviews through a longitudinal study to probe the transnational identities of this population before and during the double stigmatization; the study also examined how the mindsponge mechanism worked during the identity shifts and the interplay among stigmatization, transnational identity shifts, and the mindsponge mechanism. The study concluded that before COVID-19, Chinese international students had been stigmatized in both China and the United States

Interface formation of two- and three-dimensionally bonded materials in the case of GeTe-Sb2Te3 superlattices

GeTe–Sb2Te3 superlattices are nanostructured phase-change materials which are under intense investigation for non-volatile memory applications. They show superior properties compared to their bulk counterparts and significant efforts exist to explain the atomistic nature of their functionality. The present work sheds new light on the interface formation between GeTe and Sb2Te3, contradicting previously proposed models in the literature. For this purpose [GeTe(1 nm)–Sb2Te3(3 nm)]15 superlattices were grown on passivated Si(111) at 230 °C using molecular beam epitaxy and they have been characterized particularly with cross-sectional HAADF scanning transmission electron microscopy. Contrary to the previously proposed models, it is found that the ground state of the film actually consists of van der Waals bonded layers (i.e. a van der Waals heterostructure) of Sb2Te3 and rhombohedral GeSbTe. Moreover, it is shown by annealing the film at 400 °C, which reconfigures the superlattice into bulk rhombohedral GeSbTe, that this van der Waals layer is thermodynamically favored. These results are explained in terms of the bonding dimensionality of GeTe and Sb2Te3 and the strong tendency of these materials to intermix. The findings debate the previously proposed switching mechanisms of superlattice phase-change materials and give new insights in their possible memory application

Learning from History and Present: Next-item Recommendation via Discriminatively Exploiting User Behaviors

In the modern e-commerce, the behaviors of customers contain rich information, e.g., consumption habits, the dynamics of preferences. Recently, session-based recommendations are becoming popular to explore the temporal characteristics of customers' interactive behaviors. However, existing works mainly exploit the short-term behaviors without fully taking the customers' long-term stable preferences and evolutions into account. In this paper, we propose a novel Behavior-Intensive Neural Network (BINN) for next-item recommendation by incorporating both users' historical stable preferences and present consumption motivations. Specifically, BINN contains two main components, i.e., Neural Item Embedding, and Discriminative Behaviors Learning. Firstly, a novel item embedding method based on user interactions is developed for obtaining an unified representation for each item. Then, with the embedded items and the interactive behaviors over item sequences, BINN discriminatively learns the historical preferences and present motivations of the target users. Thus, BINN could better perform recommendations of the next items for the target users. Finally, for evaluating the performances of BINN, we conduct extensive experiments on two real-world datasets, i.e., Tianchi and JD. The experimental results clearly demonstrate the effectiveness of BINN compared with several state-of-the-art methods.Comment: 10 pages, 7 figures, KDD 201

Elemental topological ferroelectrics and polar metals of few-layer materials

Ferroelectricity can exist in elemental phases as a result of charge transfers between atoms occupying inequivalent Wyckoff positions. We investigate the emergence of ferroelectricity in two-dimensional elemental materials with buckled honeycomb lattices. Various multi-bilayer structures hosting ferroelectricity are designed by stacking-engineering. Ferroelectric materials candidates formed by group IV and V elements are predicted theoretically. Ultrathin Bi films show layer-stacking-dependent physical properties of ferroelectricity, topology, and metallicity. The two-bilayer Bi film with a polar stacking sequence is found to be an elemental topological ferroelectric material. Three and four bilayers Bi films with polar structures are ferroelectric-like elemental polar metals with topological nontrivial edge states. For Ge and Sn, trivial elemental polar metals are predicted. Our work reveals the possibility of design two-dimensional elemental topological ferroelectrics and polar metals by stacking-engineering.Comment: 18 pages, 6 figure

Copper-based charge transfer multiferroics with a d9d^9 configuration

Multiferroics are materials with a coexistence of magnetic and ferroelectric order allowing the manipulation of magnetism by applications of an electric field through magnetoelectric coupling effects. Here we propose an idea to design a class of multiferroics with a $d^9$ configuration using the magnetic order in copper-oxygen layers appearing in copper oxide high-temperature superconductors by inducing ferroelectricity. Copper-based charge transfer multiferroics SnCuO2 and PbCuO2 having the inversion symmetry breaking $P4mm$ polar space group are predicted to be such materials. The active inner s electrons in Sn and Pb hybridize with O $2p$ states leading the buckling in copper-oxygen layers and thus induces ferroelectricity, which is known as the lone pair mechanism. As a result of the $d^9$ configuration, SnCuO2 and PbCuO2 are charge transfer insulators with the antiferromagnetic ground state of the moment on Cu retaining some strongly correlated physical properties of parent compounds of copper oxide high-temperature superconductors. Our work reveals the possibility of designing multiferroics based on copper oxide high-temperature superconductors.Comment: 18 pages, 5 figures, 1 tabl

Eosinophils Instance Object Segmentation on Whole Slide Imaging Using Multi-label Circle Representation

Eosinophilic esophagitis (EoE) is a chronic and relapsing disease characterized by esophageal inflammation. Symptoms of EoE include difficulty swallowing, food impaction, and chest pain which significantly impact the quality of life, resulting in nutritional impairments, social limitations, and psychological distress. The diagnosis of EoE is typically performed with a threshold (15 to 20) of eosinophils (Eos) per high-power field (HPF). Since the current counting process of Eos is a resource-intensive process for human pathologists, automatic methods are desired. Circle representation has been shown as a more precise, yet less complicated, representation for automatic instance cell segmentation such as CircleSnake approach. However, the CircleSnake was designed as a single-label model, which is not able to deal with multi-label scenarios. In this paper, we propose the multi-label CircleSnake model for instance segmentation on Eos. It extends the original CircleSnake model from a single-label design to a multi-label model, allowing segmentation of multiple object types. Experimental results illustrate the CircleSnake model's superiority over the traditional Mask R-CNN model and DeepSnake model in terms of average precision (AP) in identifying and segmenting eosinophils, thereby enabling enhanced characterization of EoE. This automated approach holds promise for streamlining the assessment process and improving diagnostic accuracy in EoE analysis. The source code has been made publicly available at https://github.com/yilinliu610730/EoE