Long Range Intrinsic Ferromagnetism in Two Dimensional Materials and Dissipationless Future Technologies

The inherent susceptibility of low-dimensional materials to thermal fluctuations has long been expected to poses a major challenge to achieving intrinsic long-range ferromagnetic order in two-dimensional materials. The recent explosion of interest in atomically thin materials and their assembly into van der Waals heterostructures has renewed interest in two-dimensional ferromagnetism, which is interesting from a fundamental scientific point of view and also offers a missing ingredient necessary for the realization of spintronic functionality in van der Waals heterostructures. Recently several atomically thin materials have been shown to be robust ferromagnets. Such ferromagnetism is thought to be enabled by magneto crystalline anisotropy which suppresses thermal fluctuations. In this article, we review recent progress in two-dimensional ferromagnetism in detail and predict new possible two-dimensional ferromagnetic materials. We also discuss the prospects for applications of atomically thin ferromagnets in novel dissipationless electronics, spintronics, and other conventional magnetic technologies. Particularly atomically thin ferromagnets are promising to realize time reversal symmetry breaking in two-dimensional topological systems, providing a platform for electronic devices based on the quantum anomalous Hall Effect showing dissipationless transport. Our proposed directions will assist the scientific community to explore novel two-dimensional ferromagnetic families which can spawn new technologies and further improve the fundamental understanding of this fascinating area.Comment: To be appear in Applied Physics Review

The hybrid spatialities of post-industrial Beijing: communism, neoliberalism, and brownfield redevelopment

While the redevelopment of urban brownfield sites in China has received much attention, the role of political ideology in this process is usually downplayed or sidelined to a set of stylized assumptions. This paper invites giving a greater analytical focus to the evolving and nonorthodox nature of China’s politico-ideological model as a factor shaping urban change and redevelopment. The paper provides an analytical framework integrating multi-level and evolutionary perspectives while exploring the experiences of the formation and post-industrial redevelopment of brownfield sites in Beijing. The analysis demonstrates that neoliberal economic policies and the communist political doctrine are co-constitutive in the production of China’s post-industrial urban space. This produces a sense of spatial hybridity that combines and co-embeds what may be assumed to be mutually exclusive

Alpha and beta diversity of functional traits in subtropical evergreen broad-leaved secondary forest communities

IntroductionIntra-speciic variation is the main source of functional trait diversity and has similar ecological effects as inter-speciic variation.MethodsWe studied 79 species and 3546 individuals from 50 ixed monitoring plots in subtropical evergreen broad - leaved secondary forests in Zhejiang Province, China. Using trait gradient analysis, we examined nine traits (speciic leaf area, leaf dry matter content, wood density, leaf area, chlorophyll content, leaf nitrogen content, leaf phosphorus content, leaf potassium content, and nitrogen-phosphorus ratio) by decomposing species functional traits into alpha (within-community) and beta (among-communities) measure the impact of environmental gradients and the presence of other species on the variation of traits.ResultAll nine functional traits showed some degree of differentiation in the forest communities, with a greater range of variation in alpha values than in beta values . Correlations were signiicantly different between the trait differences in the communities. The alpha values of each trait showed a higher correlation with other components than the beta values. The factors affecting intra-speciic trait variation were relatively complex. The alpha component had a more signiicant and stronger effect on intra-speciic trait variation compared to the beta component. Abiotic factors, such as soil nutrient content, soil nitrogen-phosphorus content, directly affected the beta component. In contrast, biotic factors, such as tree height variation, had a direct and stronger effect on the alpha component.DiscussionOur results demonstrate that alpha and beta components, as independent differentiation axes among coexisting species, have different sensitivities to different environmental factors and traits in different ecological strategies and spatial scales. Trait gradient analysis can more clearly reveal the variation patterns of species traits in communities, which will help to understand the scale effects and potential mechanisms of trait relationships

Preparation and Characterisation of Nobiletin-Loaded Nanostructured Lipid Carriers

The objective of this manuscript was to investigate and optimise the potential of nanostructured lipid carriers (NLCs) as a carrier system for nobiletin (NOB), which was prepared by high-pressure homogenisation method. Additionally, this study was focused on the application of NOB-loaded NLC (NOB-NLC) in functional food. Response surface method with a three-level Box–Behnken design was validated through analysis of variance, and the robustness of the design was confirmed through the correspondence between the values measured in the experiments and the predicted ones. Properties of the prepared NOB-NLC, such as Z-average, polydispersity, entrapment efficiency, zeta potential, morphology, and crystallinity, were investigated. NOB-NLC exhibited a spherical shape with a diameter of 112.27 ± 5.33 nm, zeta potential of −35.1 ± 2.94 mV, a polydispersity index of 0.251 ± 0.058, and an EE of 81.06%  ±  6.02%. Results from X-ray diffraction and differential scanning calorimetry of NOB-NLC reviewed that the NOB crystal might be converted to an amorphous state. Fourier transform infrared spectroscopic analysis demonstrated that chemical interaction was absent between the compound and lipid mixture in NOB-NLC

Sample-Balanced and IoU-Guided Anchor-Free Visual Tracking

Siamese network-based visual tracking algorithms have achieved excellent performance in recent years, but challenges such as fast target motion, shape and scale variations have made the tracking extremely difficult. The regression of anchor-free tracking has low computational complexity, strong real-time performance, and is suitable for visual tracking. Based on the anchor-free siamese tracking framework, this paper firstly introduces balance factors and modulation coefficients into the cross-entropy loss function to solve the classification inaccuracy caused by the imbalance between positive and negative samples as well as the imbalance between hard and easy samples during the training process, so that the model focuses more on the positive samples and the hard samples that make the major contribution to the training. Secondly, the intersection over union (IoU) loss function of the regression branch is improved, not only focusing on the IoU between the predicted box and the ground truth box, but also considering the aspect ratios of the two boxes and the minimum bounding box area that accommodate the two, which guides the generation of more accurate regression offsets. The overall loss of classification and regression is iteratively minimized and improves the accuracy and robustness of visual tracking. Experiments on four public datasets, OTB2015, VOT2016, UAV123 and GOT-10k, show that the proposed algorithm achieves the state-of-the-art performance

A decentralized mechanism based on differential privacy for privacy-preserving computation in smart grid

As one of the most successful industrial realizations of Internet of Things, a smart grid is a smart IoT system that deploys widespread smart meters to capture fine-grained data on residential power usage. Unfortunately, it always suffers diverse privacy attacks, which seriously increases the risk of violating the privacy of customers. Although some solutions have been proposed to address this privacy issue, most of them mainly rely on a trusted party and focus on the sanitization of metering masurements. Moreover, these solutions are vulnerable to advanced attacks. In this paper, we propose a decentralized mechanism for privacy-preserving computation in smart grid called DDP, which leaverages the differential privacy and extends the data sanitization from the value domain to the time domain. Specifically, we inject Laplace noise to the measurements at the end of each customer in a distributed manner, and then use a random permutation algorithm to shuffle the power measurement sequence, thereby enforcing differential privacy after aggregation and preventing the sensitive power usage mode informaton of the customers from being inferred by other parties. Extensive experiments demonstrate that DDP shows an outstanding performance in terms of privacy from the non-intrusive load monitoring (NILM) attacks and utility by using two different error analysis