113 research outputs found

    On the Performance Trade-off of Distributed Integrated Sensing and Communication Networks

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    In this letter, we analyze the performance trade-off in distributed integrated sensing and communication (ISAC) networks. Specifically, with the aid of stochastic geometry theory, we derive the probability of detection of that of the coverage given user number. Based on the analytical derivations, we provide a quantitative description of the performance limits and the performance trade-off between sensing and communication in a distributed ISAC network under the given transmit power and bandwidth budget. Extensive simulations are conducted and the numerical results validate the accuracy of our derivations

    Modulating effects of interactional contexts on bilinguals’ cognitive control: Evidence for the Adaptive Control Hypothesis

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    AIMS & OBJECTS: The Adaptive Control Hypothesis (ACH) proposed that different interactional contexts place different demands on cognitive processes for bilinguals. However, how cognitive control processes dynamically adapt to comprehending and producing languages in different interactional contexts is still poorly understood. This study investigated how different language interactional contexts (i.e., single-language, dual-language, and dense code-switching) modulate cognitive control in bilingual language comprehension. METHODOLOGY:Inhibitory control in 36 Chinese -English bilinguals was examined through flanker tasks. Participants’ language and cognitive control statuses in the three interactional contexts were manipulated through three different types of dialogue-listening. After they listened to each type of dialogue, they were instructed to complete the flanker task and answer 10 comprehension questions related to the dialogue. DATA AND ANALYSIS: Repeated-measures analysis of variance (ANOVA) compared participants’ reaction times and response accuracy in flanker tasks across the three interactional contexts. Similarly, their language comprehension performances across different interactional contexts were also compared. FINDING/CONCLUSIONS: Both the dual-language and Chinese single-language contexts showed significant facilitatory effects on participants’ inhibitory control efficiency. Furthermore, participants performed more accurately on answering comprehension questions in the Chinese single-language context, indicating the dominant language effects on modulating bilinguals’ language comprehension performance. Such effects were not found in the dense code-switching and dual-language contexts. ORIGINALITY: This study provided empirical evidence for the facilitatory effects of dual-language contexts on cognitive control in bilingual language comprehension process, which further extends the ACH to bilingual’s cognitive process associated with language comprehension. SIGNIFICANCE/IMPLICATIONS: In general, it is an attempt to explore the associations between interactional contexts and cognitive control through bilingual language and cognitive processing manipulations

    DAT++: Spatially Dynamic Vision Transformer with Deformable Attention

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    Transformers have shown superior performance on various vision tasks. Their large receptive field endows Transformer models with higher representation power than their CNN counterparts. Nevertheless, simply enlarging the receptive field also raises several concerns. On the one hand, using dense attention in ViT leads to excessive memory and computational cost, and features can be influenced by irrelevant parts that are beyond the region of interests. On the other hand, the handcrafted attention adopted in PVT or Swin Transformer is data agnostic and may limit the ability to model long-range relations. To solve this dilemma, we propose a novel deformable multi-head attention module, where the positions of key and value pairs in self-attention are adaptively allocated in a data-dependent way. This flexible scheme enables the proposed deformable attention to dynamically focus on relevant regions while maintains the representation power of global attention. On this basis, we present Deformable Attention Transformer (DAT), a general vision backbone efficient and effective for visual recognition. We further build an enhanced version DAT++. Extensive experiments show that our DAT++ achieves state-of-the-art results on various visual recognition benchmarks, with 85.9% ImageNet accuracy, 54.5 and 47.0 MS-COCO instance segmentation mAP, and 51.5 ADE20K semantic segmentation mIoU.Comment: 17 pages, 6 figures, 11 table

    Is Blockchain for Internet of Medical Things a Panacea for COVID-19 Pandemic?

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    The outbreak of the COVID-19 pandemic has deeply influenced the lifestyle of the general public and the healthcare system of the society. As a promising approach to address the emerging challenges caused by the epidemic of infectious diseases like COVID-19, Internet of Medical Things (IoMT) deployed in hospitals, clinics, and healthcare centers can save the diagnosis time and improve the efficiency of medical resources though privacy and security concerns of IoMT stall the wide adoption. In order to tackle the privacy, security, and interoperability issues of IoMT, we propose a framework of blockchain-enabled IoMT by introducing blockchain to incumbent IoMT systems. In this paper, we review the benefits of this architecture and illustrate the opportunities brought by blockchain-enabled IoMT. We also provide use cases of blockchain-enabled IoMT on fighting against the COVID-19 pandemic, including the prevention of infectious diseases, location sharing and contact tracing, and the supply chain of injectable medicines. We also outline future work in this area.Comment: 15 pages, 8 figure

    Development of a fibroblast activation protein-targeted PET/NIR dual-modality probe and its application in head and neck cancer

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    Purpose: The combination of near-infrared (NIR) and positron emission tomography (PET) imaging presents an opportunity to utilize the benefits of dual-modality imaging for tumor visualization. Based on the observation that fibroblast activation protein (FAP) is upregulated in cancer-associated fibroblasts (CAFs) infiltrating all solid tumors, including head and neck squamous cell carcinoma (HNSCC), we developed the novel PET/NIR probe [68Ga]Ga-FAP-2286-ICG. Preclinically, the specificity, biodistribution and diagnostic properties were evaluated.Methods: Cell uptake assays were completed with the U87MG cell to evaluate the specificity of the [68Ga]Ga-FAP-2286-ICG. The tumor-targeting efficiency, biodistribution and optimal imaging time window of the [68Ga]Ga-FAP-2286-ICG were studied in mice bearing U87MG xenografts. HNSCC tumor-bearing mice were used to evaluate the feasibility of [68Ga]Ga-FAP-2286-ICG for tumor localization and guided surgical resection of HNSCC tumors.Results: The in vitro experiments confirmed that [68Ga]Ga-FAP-2286-ICG showed good stability, specific targeting of the probe to FAP, and the durable retention effect in high-expressing FAP tumors U87MG cell. Good imaging properties such as good tumor uptake, high tumor-to-background ratios (5.44 ± 0.74) and specificity, and tumor contouring were confirmed in studies with mice bearing the U87MG xenograft. PET/CT imaging of the probe in head and neck cancer-bearing mice demonstrated specific uptake of the probe in the tumor with a clear background. Fluorescence imaging further validated the value of the probe in guiding surgical resection and achieving precise removal of the tumor and residual lesions.Conclusion: In a preclinical model, these attractive [68Ga]Ga-FAP-2286-ICG PET/NIR imaging acquired in head and neck cancer make it a promising FAP-targeted multimodal probe for clinical translation

    Securing internet of medical things with friendly-jamming schemes

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    The Internet of Medical Things (IoMT)-enabled e-healthcare can complement traditional medical treatments in a flexible and convenient manner. However, security and privacy become the main concerns of IoMT due to the limited computational capability, memory space and energy constraint of medical sensors, leading to the in-feasibility for conventional cryptographic approaches, which are often computationally-complicated. In contrast to cryptographic approaches, friendly jamming (Fri-jam) schemes will not cause extra computing cost to medical sensors, thereby becoming potential countermeasures to ensure security of IoMT. In this paper, we present a study on using Fri-jam schemes in IoMT. We first analyze the data security in IoMT and discuss the challenges. We then propose using Fri-jam schemes to protect the confidential medical data of patients collected by medical sensors from being eavesdropped. We also discuss the integration of Fri-jam schemes with various communication technologies, including beamforming, Simultaneous Wireless Information and Power Transfer (SWIPT) and full duplexity. Moreover, we present two case studies of Fri-jam schemes in IoMT. The results of these two case studies indicate that the Fri-jam method will significantly decrease the eavesdropping risk while leading to no significant influence on legitimate transmission
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