6G Non-Terrestrial Networks Enabled Low-Altitude Economy: Opportunities and Challenges

The unprecedented development of non-terrestrial networks (NTN) utilizes the low-altitude airspace for commercial and social flying activities. The integration of NTN and terres- trial networks leads to the emergence of low-altitude economy (LAE). A series of LAE application scenarios are enabled by the sensing, communication, and transportation functionalities of the aircrafts. The prerequisite technologies supporting LAE are introduced in this paper, including the network coverage and aircrafts detection. The LAE functionalities assisted by aircrafts with respect to sensing and communication are then summarized, including the terrestrial and non-terrestrial targets sensing, ubiquitous coverage, relaying, and traffic offloading. Finally, several future directions are identified, including aircrafts collaboration, energy efficiency, and artificial intelligence enabled LAE.Comment: This paper has been submitted to IEEE for possible publicatio

Towards Relating Fragile-To-Strong Transition to Fragile Glass

Glass formers are in general classified as strong or fragile depending on whether their relaxation rates follow Arrhenius or super-Arrhenius temperature dependence. There are however notable exceptions such as water, which exhibit a fragile-to-strong (FTS) transition and behave as fragile and strong respectively at high and low temperatures. In this work, the FTS transition is studied using a distinguishable-particle lattice model previously demonstrated to be capable of simulating both strong and fragile glasses [Phys. Rev. Lett. 125, 265703 (2020)]. Starting with a bimodal pair-interaction distribution appropriate for fragile glasses, we show that by narrowing down the energy dispersion in the low-energy component of the distribution, a FTS transition is observed. The transition occurs at a temperature at which the stretching exponent of the relaxation is minimized, in agreement with previous molecular dynamics simulations

Serum YKL-40 in coronary heart disease: linkage with inflammatory cytokines, artery stenosis, and optimal cut-off value for estimating major adverse cardiovascular events

ObjectiveYKL-40, previously known as chitinase-3-like protein 1 (CHI3L1), is an inflammation-related glycoprotein that promotes atherosclerosis, but its application and optimal cut-off value as a prognostic biomarker in coronary heart disease (CHD) require more clinical evidence. Thus, this prospective study aimed to evaluate the linkage of serum YKL-40 with disease features, inflammatory cytokines, and major adverse cardiovascular events (MACEs) in CHD patients.MethodsA total of 410 CHD patients were enrolled for serum YKL-40 determination via enzyme-linked immunosorbent assay. Meanwhile, serum YKL-40 levels in 100 healthy controls (HCs) were also quantified.ResultsYKL-40 level was higher in CHD patients compared with that in HCs (P < 0.001). YKL-40 was positively linked with hyperlipidemia (P = 0.014), diabetes mellitus (P = 0.001), fasting blood glucose (P = 0.045), C-reactive protein (P < 0.001), the Gensini score (P < 0.001), and stenosis degree (graded by the Gensini score) (P < 0.001) in CHD patients. In addition, an elevated YKL-40 level was associated with increased levels of tumor necrosis factor alpha (P = 0.001), interleukin (IL)-1β (P = 0.001), IL-6 (P < 0.001), and IL-17A (P = 0.002) in CHD patients. The 1-/2-/3-year cumulative MACE rates of CHD patients were 5.5%, 14.4%, and 25.0%, respectively. Regarding the prognostic capability, YKL-40 ≥100 ng/ml (the median cut-off value) (P = 0.003) and YKL-40 ≥150 ng/ml (the third interquartile cut-off value) (P = 0.021) reflected an elevated accumulating MACE rate, whereas accumulating MACE was not different between CHD patients with YKL-40 ≥80 and <80 ng/ml (the first interquartile cut-off value) (P = 0.083).ConclusionSerum YKL-40 is positively linked with inflammatory cytokines and the Gensini score, whose high expression cut-off by 100 and 150 ng/ml estimates a higher MACE risk in CHD patients

GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training

Cross-modal pre-training has shown impressive performance on a wide range of downstream tasks, benefiting from massive image-text pairs collected from the Internet. In practice, online data are growing constantly, highlighting the importance of the ability of pre-trained model to learn from data that is continuously growing. Existing works on cross-modal pre-training mainly focus on training a network with fixed architecture. However, it is impractical to limit the model capacity when considering the continuously growing nature of pre-training data in real-world applications. On the other hand, it is important to utilize the knowledge in the current model to obtain efficient training and better performance. To address the above issues, in this paper, we propose GrowCLIP, a data-driven automatic model growing algorithm for contrastive language-image pre-training with continuous image-text pairs as input. Specially, we adopt a dynamic growth space and seek out the optimal architecture at each growth step to adapt to online learning scenarios. And the shared encoder is proposed in our growth space to enhance the degree of cross-modal fusion. Besides, we explore the effect of growth in different dimensions, which could provide future references for the design of cross-modal model architecture. Finally, we employ parameter inheriting with momentum (PIM) to maintain the previous knowledge and address the issue of the local minimum dilemma. Compared with the existing methods, GrowCLIP improves 2.3% average top-1 accuracy on zero-shot image classification of 9 downstream tasks. As for zero-shot image retrieval, GrowCLIP can improve 1.2% for top-1 image-to-text recall on Flickr30K dataset.Comment: Accepted by ICCV202

Loss of Abhd5 Promotes Colorectal Tumor Development and Progression by Inducing Aerobic Glycolysis and Epithelial-Mesenchymal Transition

How cancer cells shift metabolism to aerobic glycolysis is largely unknown. Here, we show that deficiency of a/b-hydrolase domain-containing 5 (Abhd5), an intracellular lipolytic activator that is also known as comparative gene identification 58 (CGI-58), promotes this metabolic shift and enhances malignancies of colorectal carcinomas (CRCs). Silencing of Abhd5 in normal fibroblasts induces malignant transformation. Intestine-specific knockout of Abhd5 in ApcMin/+ mice robustly increases tumorigenesis and malignant transformation of adenomatous polyps. In colon cancer cells, Abhd5 deficiency induces epithelial-mesenchymal transition by suppressing the AMPKa-p53 pathway, which is attributable to increased aerobic glycolysis. In human CRCs, Abhd5 expression falls substantially and correlates negatively with malignant features. Our findings link Abhd5 to CRC pathogenesis and suggest that cancer cells develop aerobic glycolysis by suppressin

The role of vimentin in regulating cell-invasive migration in dense cultures of breast carcinoma cells

Cell migration and mechanics are tightly regulated by the integrated activities of the various cytoskeletal networks. In cancer cells, cytoskeletal modulations have been implicated in the loss of tissue integrity, and acquisition of an invasive phenotype. In epithelial cancers, for example, increased expression of the cytoskeletal filament protein vimentin correlates with metastatic potential. Nonetheless, the exact mechanism whereby vimentin affects cell motility remains poorly understood. In this study, we measured the effects of vimentin expression on the mechano-elastic and migratory properties of the highly invasive breast carcinoma cell line MDA231. We demonstrate here that vimentin stiffens cells and enhances cell migration in dense cultures, but exerts little or no effect on the migration of sparsely plated cells. These results suggest that cell-cell interactions play a key role in regulating cell migration, and coordinating cell movement in dense cultures. Our findings pave the way towards understanding the relationship between cell migration and mechanics, in a biologically relevant context.Comment: 26+21 pages, 6+11 figures, supplementary movies available at http://doi.org/10.6084/m9.figshare.5480149, submitted to Nano Letters journa

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve