175 research outputs found

    Applications of Federated Learning in Smart Cities: Recent Advances, Taxonomy, and Open Challenges

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    Federated learning plays an important role in the process of smart cities. With the development of big data and artificial intelligence, there is a problem of data privacy protection in this process. Federated learning is capable of solving this problem. This paper starts with the current developments of federated learning and its applications in various fields. We conduct a comprehensive investigation. This paper summarize the latest research on the application of federated learning in various fields of smart cities. In-depth understanding of the current development of federated learning from the Internet of Things, transportation, communications, finance, medical and other fields. Before that, we introduce the background, definition and key technologies of federated learning. Further more, we review the key technologies and the latest results. Finally, we discuss the future applications and research directions of federated learning in smart cities

    Characterization of ascorbate-glutathione cycle response in Zostera marina seedlings under short-term temperature surge

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    The ascorbate-glutathione (AsA-GSH) cycle plays a critical role in scavenging hydrogen peroxide in plants and contributes significantly to plant stress tolerance. This study examines the cycle’s response in Zostera marina seedlings to warming, specifically under conditions of abnormal sea temperature increase. Three temperature gradients were established: 18°C (control group), 23°C (high-temperature group), and 28°C (abnormally high-temperature group). Results after 7 days of exposure to mild high temperature (23°C) showed decreased MDA content in the HT group, increased AsA/DHA ratio, and enhanced activity of enzymes related to the AsA-GSH cycle. However, exposure to extreme high temperatures resulted in increased oxidative damage and redox imbalance in the AHT group. Initially, enzymes associated with the AsA-GSH cycle, such as APX, MDHAR, GPX, and γ-ECS, increased but significantly decreased later under stress. In contrast, DHAR and GaILDH levels significantly rose on the seventh day. Transcriptome analysis revealed upregulation of APX, MDHAR, DHAR, GR, and γ-ECS genes in the HT group, with a decline in other enzyme gene expressions by the seventh day, except for APX. Under extreme high temperatures, APX expression was downregulated early in the stress period, while DHAR was upregulated, indicating Z. marina seedlings can mitigate oxidative damage under short-term high temperatures by activating the AsA-GSH cycle. Conversely, extreme high temperatures may inhibit this cycle, disrupt redox balance, and adversely affect Z. marina seedling establishment, potentially leading to their demise

    Seasonal temperature variation in Zostera marina seedlings under ocean acidification

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    ObjectiveTo investigate the responses of Zostera marina seedlings to the individual and combined stresses of seasonal temperature increase and ocean acidification (OA) caused by global climate change and anthropogenic factors. This data will help in efforts to protect and restore seagrass beds in temperate coastal zones of China.MethodsA mesoscale experimental system was utilized to analyze stress response mechanisms at multiple levels - phenotype, transcriptome, and metabolome - during the seedling stage of Z. marina, a dominant temperate seagrass species in China. The study monitored the seedlings under varying conditions: increased seasonal temperature, OA, and a combination of both.ResultsFindings revealed that under high-temperature conditions, carotenoid biosynthesis was stimulated through the upregulation of specific metabolites and enzymes. Similarly, the biosynthesis of certain alkaloids was promoted alongside modifications in starch, sucrose, and nitrogen metabolism, which improved the plant’s adaptation to OA. Unique metabolic pathways were activated under OA, including the degradation of certain amino acids and modifications in the citric acid cycle and pyruvate metabolism. When subjected to both temperature and OA stresses, seedlings actively mobilized various biosynthetic pathways to enhance adaptability and resilience, with distinct metabolic pathways enhancing the plant’s response under diversified stress conditions. In terms of growth, all treatment groups exhibited significant leaf length increase (p < 0.05), but the weakest growth index was observed under combined stress, followed by the thermal treatment group. Conversely, growth under OA treatment was better, showing a significant increase in wet weight, leaf length, and leaf width (p < 0.05).ConclusionSeasonal temperature increase was found to inhibit the growth of Z. marina seedlings to some extent, while OA facilitated their growth. However, the positive effects of OA did not mitigate the damage caused by increased seasonal temperature under combined stress due to seedlings’ sensitivity at this stage. Our findings elucidate differing plant coping strategies under varied stress conditions, contingent on the initial environment. This research anticipates providing significant data support for the adaptation of Z. marina seedlings to seasonal temperature fluctuations and global oceanic events like OA, propelling the effective conservation of seagrass beds

    Conceptual design and progress of transmitting ∼\sim MV DC HV into 4 K LHe detectors

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    A dual-phase TPC (Time Projection Chamber) is more advanced in characterizing an event than a single-phase one because it can, in principle, reconstruct the 3D (X-Y-Z) image of the event, while a single-phase detector can only show a 2D (X-Y) picture. As a result, more enriched physics is expected for a dual-phase detector than a single-phase one. However, to build such a detector, DC HV (High Voltage) must be delivered into the chamber (to have a static electric field), which is a challenging task, especially for an LHe detector due to the extremely low temperature, ∼\sim 4 K, and the very high voltage, ∼\sim MV (Million Volts). This article introduces a convincing design for transmitting ∼\sim MV DC into a 4 K LHe detector. We also report the progress of manufacturing a 100 kV DC feedthrough capable of working at 4 K. Surprisingly, we realized that the technology we developed here might be a valuable reference to the scientists and engineers aiming to build residential bases on the Moon or Mars

    Searching for ER and/or NR-like dark matter signals with the especially low background liquid helium TPCs

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    In the Dark Matter (DM) direct detection community, the absence of convincing signals has become a ``new normal'' for decades. Among other possibilities, the ``new normal'' might indicate that DM-matter interactions could generate not only the hypothetical NR (Nuclear Recoil) events but also the ER (Electron Recoil) ones, which have often been tagged as backgrounds historically. Further, we argue that ER and NR-like DM signals could co-exist in a DM detector's same dataset. So in total, there would be three scenarios we can search for DM signals: (i) ER excess only, (ii) NR excess only, and (iii) ER and NR excesses combined. To effectively identify any possible DM signal under the three scenarios, a DM detector should (a) have the minimum ER and NR backgrounds and (b) be capable of discriminating ER events from NR ones. Accordingly, we introduce the newly established project, ALETHEIA, which implements liquid helium-filled TPCs (Time Projection Chamber) in hunting for DM. Thanks to the nearly single-digit number of ER and NR backgrounds on 1 ton*yr exposure, presumably, the ALETHEIA detectors should be able to identify any form of DM-induced excess in its ROI (Research Of Interest). As far as we know, ALETHEIA is the first DM direct detection experiment claiming such an inclusive search; conventional detectors search DM mainly on the ``ER excess only'' and/or the ``NR excess only'' channel, not the ``ER and NR excesses combined'' channel. In addition, we introduce a preliminary scheme to one of the most challenging R\&D tasks, transmitting 500+ kV into a 4 K LHe detector

    High Expression of DEPDC1 Promotes Malignant Phenotypes of Breast Cancer Cells and Predicts Poor Prognosis in Patients With Breast Cancer

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    DEP domain containing 1 (DEPDC1) is a novel tumor-associated gene, which is aberrantly expressed in multiple types of cancer and involves in tumorigenesis and cancer progression. Here, we examined the functional involvement and underlying mechanism of DEPDC1 in breast cancer. In this study, the immunohistochemistry results demonstrated that DEPDC1 was high-expressed in breast cancer tissues compared with the paired adjacent normal breast tissues, and its tendency at protein level was consistent with mRNA level from TCGA data. Moreover, DEPDC1 mRNA level revealed the strongest association with poor prognosis and development in breast cancer. In vitro assays showed that DEPDC1 overexpression resulted in significant promotion of proliferation by regulating cell cycle in MCF-7 cells, whilst an opposite effect was found in the MDA-MB-231 cells with DEPDC1 deletion. Notably, further investigation indicated DEPDC1's ability of promoting breast cancer cells migration and invasion. In addition, we discovered that DEPDC1 caused hyper-activation of PI3K/AKT/mTOR signaling in breast cancer cells. Therefore, the increased DEPDC1 expression in breast cancer is correlated with disease progression and poor survival, which suggested that DEPDC1 might be a potential therapeutic target against this disease

    Dissecting Tumor Antigens and Immune Subtypes of Glioma to Develop mRNA Vaccine

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    Background Nowadays, researchers are leveraging the mRNA-based vaccine technology used to develop personalized immunotherapy for cancer. However, its application against glioma is still in its infancy. In this study, the applicable candidates were excavated for mRNA vaccine treatment in the perspective of immune regulation, and suitable glioma recipients with corresponding immune subtypes were further investigated. Methods The RNA-seq data and clinical information of 702 and 325 patients were recruited from TCGA and CGGA, separately. The genetic alteration profile was visualized and compared by cBioPortal. Then, we explored prognostic outcomes and immune correlations of the selected antigens to validate their clinical relevance. The prognostic index was measured via GEPIA2, and infiltration of antigen-presenting cells (APCs) was calculated and visualized by TIMER. Based on immune-related gene expression, immune subtypes of glioma were identified using consensus clustering analysis. Moreover, the immune landscape was visualized by graph learning-based dimensionality reduction analysis. Results Four glioma antigens, namely ANXA5, FKBP10, MSN, and PYGL, associated with superior prognoses and infiltration of APCs were selected. Three immune subtypes IS1–IS3 were identified, which fundamentally differed in molecular, cellular, and clinical signatures. Patients in subtypes IS2 and IS3 carried immunologically cold phenotypes, whereas those in IS1 carried immunologically hot phenotype. Particularly, patients in subtypes IS3 and IS2 demonstrated better outcomes than that in IS1. Expression profiles of immune checkpoints and immunogenic cell death (ICD) modulators showed a difference among IS1–IS3 tumors. Ultimately, the immune landscape of glioma elucidated considerable heterogeneity not only between individual patients but also within the same immune subtype. Conclusions ANXA5, FKBP10, MSN, and PYGL are identified as potential antigens for anti-glioma mRNA vaccine production, specifically for patients in immune subtypes 2 and 3. In summary, this study may shed new light on the promising approaches of immunotherapy, such as devising mRNA vaccination tailored to applicable glioma recipients

    Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network

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    The capabilities of magnetic resonance imaging (MRI) to measure structural and functional connectivity in the human brain have motivated growing interest in characterizing the relationship between these measures in the distributed neural networks of the brain. In this study, we attempted an integration of structural and functional analyses of the human language circuits, including Wernicke's (WA), Broca's (BA) and supplementary motor area (SMA), using a combination of blood oxygen level dependent (BOLD) and diffusion tensor MRI.Functional connectivity was measured by low frequency inter-regional correlations of BOLD MRI signals acquired in a resting steady-state, and structural connectivity was measured by using adaptive fiber tracking with diffusion tensor MRI data. The results showed that different language pathways exhibited different structural and functional connectivity, indicating varying levels of inter-dependence in processing across regions. Along the path between BA and SMA, the fibers tracked generally formed a single bundle and the mean radius of the bundle was positively correlated with functional connectivity. However, fractional anisotropy was found not to be correlated with functional connectivity along paths connecting either BA and SMA or BA and WA. for use in diagnosing and determining disease progression and recovery

    Tubeless video-assisted thoracic surgery for pulmonary ground-glass nodules: expert consensus and protocol (Guangzhou)

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