23 research outputs found

    Accelerating Split Federated Learning over Wireless Communication Networks

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    The development of artificial intelligence (AI) provides opportunities for the promotion of deep neural network (DNN)-based applications. However, the large amount of parameters and computational complexity of DNN makes it difficult to deploy it on edge devices which are resource-constrained. An efficient method to address this challenge is model partition/splitting, in which DNN is divided into two parts which are deployed on device and server respectively for co-training or co-inference. In this paper, we consider a split federated learning (SFL) framework that combines the parallel model training mechanism of federated learning (FL) and the model splitting structure of split learning (SL). We consider a practical scenario of heterogeneous devices with individual split points of DNN. We formulate a joint problem of split point selection and bandwidth allocation to minimize the system latency. By using alternating optimization, we decompose the problem into two sub-problems and solve them optimally. Experiment results demonstrate the superiority of our work in latency reduction and accuracy improvement

    Fake News Detection with Heterogeneous Transformer

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    The dissemination of fake news on social networks has drawn public need for effective and efficient fake news detection methods. Generally, fake news on social networks is multi-modal and has various connections with other entities such as users and posts. The heterogeneity in both news content and the relationship with other entities in social networks brings challenges to designing a model that comprehensively captures the local multi-modal semantics of entities in social networks and the global structural representation of the propagation patterns, so as to classify fake news effectively and accurately. In this paper, we propose a novel Transformer-based model: HetTransformer to solve the fake news detection problem on social networks, which utilises the encoder-decoder structure of Transformer to capture the structural information of news propagation patterns. We first capture the local heterogeneous semantics of news, post, and user entities in social networks. Then, we apply Transformer to capture the global structural representation of the propagation patterns in social networks for fake news detection. Experiments on three real-world datasets demonstrate that our model is able to outperform the state-of-the-art baselines in fake news detection

    Degradation, isomerization and stabilization of three dicaffeoylquinic acids under ultrasonic treatment at different pH

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    Dicaffeoylquinic acids (diCQAs) are found in a variety of edible and medicinal plants with various biological activities. An important issue is the low stability of diCQAs during extraction and food processing, resulting in the degradation and transformation. This work used 3,5-diCQA as a representative to study the influence of different parameters in ultrasonic treatment on the stability of diCQAs, including solvent, temperature, treatment time, ultrasonic power, duty cycle, and probe immersion depth. The generation of free radicals and its influence were investigated during the treatment. The stability of three diCQAs (3,5-diCQA, 4,5-diCQA and 3,4-diCQA) under the certain ultrasonic condition at different pH conditions was evaluated and found to decrease with the increase of pH, further weakened by ultrasonic treatment. Ultrasound was found to accelerate the degradation and isomerization of diCQAs. Different diCQAs showed different pattern of degradation and isomerization. The stability of diCQAs could be improved by adding epigallocatechin gallate and vitamin C

    The Mediating Role of Cumulative Fatigue on the Association between Occupational Stress and Depressive Symptoms: A Cross-Sectional Study among 1327 Chinese Primary Healthcare Professionals

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    Occupational stress and depressive symptoms are common among professionals in the primary healthcare system, and the former can lead to a more severe level of the latter. However, there are few studies on the mediating effect of occupational stress on depressive symptoms using cumulative fatigue as a mediating variable. The Core Occupational Stress Scale, the Self Diagnosis Scale of Workers’ Cumulative Fatigue, and the Patient Health Questionnaire were used in the proposed study. To analyze and test the mediating effect, the hierarchical regression analysis method and the Bootstrap method were applied. Our results showed that occupational stress was positively correlated with the level of cumulative fatigue (p p p p p p p < 0.001), respectively, while the percentages of the mediating effects were 43.56%, 44.46%, 48.58%, 71.26%, and 45.80%, respectively. Occupational stress can directly or indirectly affect depressive symptoms through the mediating effect of cumulative fatigue. Therefore, primary healthcare professionals can reduce occupational stress, which in turn relieves depressive symptoms, and thus reduce cumulative fatigue levels

    Graphene Hydrogel as a Porous Scaffold for Cartilage Regeneration

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    Porous scaffolds have widely been exploited in cartilage tissue regeneration. However, it is often difficult to understand how the delicate hierarchical structure of the scaffold material affects the regeneration process. Graphene materials are versatile building blocks for robust and biocompatible porous structures, enabling investigation of structural cues on tissue regeneration otherwise challenging to ascertain. Here, we utilize a graphene hydrogel with stable and tunable structure as a model scaffold to examine the effect of porous structure on matrix remodeling associated with ingrowth of chondrocytes on scaffolds. We observe much-accelerated yet balanced cartilage remodeling correlating the ingrowth of chondrocytes into the graphene scaffold with an open pore structure on the surface. Importantly, such an enhanced remodeling selectively promotes the expression of collagen type II fibrils over proteoglycan aggrecan, hence clearly illustrating that chondrocytes maintain a stable phenotype when they migrate into the scaffold while offering new insights into scaffold design for cartilage repair

    Exposure to 3,3′,5-triiodothyronine affects histone and RNA polymerase II modifications, but not DNA methylation status, in the regulatory region of the Xenopus laevis thyroid hormone receptor βΑ gene

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    NOTICE: this is the author’s version of a work that was accepted for publication in Biochemical and Biophysical Research Communications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Biochemical and Biophysical Research Communications, Volume 467, Issue 1, 6 November 2015, 10.1016/j.bbrc.2015.09.132autho
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