A Case Study of Edge Computing Implementations: Multi-access Edge Computing, Fog Computing and Cloudlet

With the explosive growth of intelligent and mobile devices, the current centralized cloud computing paradigm is encountering difficult challenges. Since the primary requirements have shifted towards implementing real-time response and supporting context awareness and mobility, there is an urgent need to bring resources and functions of centralized clouds to the edge of networks, which has led to the emergence of the edge computing paradigm. Edge computing increases the responsibilities of network edges by hosting computation and services, therefore enhancing performances and improving quality of experience (QoE). Fog computing, multi-access edge computing (MEC), and cloudlet are three typical and promising implementations of edge computing. Fog computing aims to build a system that enables cloud-to-thing service connectivity and works in concert with clouds, MEC is seen as a key technology of the fifth generation (5G) system, and Cloudlet is a micro-data center deployed in close proximity. In terms of deployment scenarios, Fog computing focuses on the Internet of Things (IoT), MEC mainly provides mobile RAN application solutions for 5G systems, and cloudlet offloads computing power at the network edge. In this paper, we present a comprehensive case study on these three edge computing implementations, including their architectures, differences, and their respective application scenario in IoT, 5G wireless systems, and smart edge. We discuss the requirements, benefits, and mechanisms of typical co-deployment cases for each paradigm and identify challenges and future directions in edge computing

PLGA-based gene delivering nanoparticle enhance suppression effect of miRNA in HePG2 cells

The biggest challenge in the field of gene therapy is how to effectively deliver target genes to special cells. This study aimed to develop a new type of poly(D,L-lactide-co-glycolide) (PLGA)-based nanoparticles for gene delivery, which are capable of overcoming the disadvantages of polyethylenimine (PEI)- or cationic liposome-based gene carrier, such as the cytotoxicity induced by excess positive charge, as well as the aggregation on the cell surface. The PLGA-based nanoparticles presented in this study were synthesized by emulsion evaporation method and characterized by transmission electron microscopy, dynamic light scattering, and energy dispersive spectroscopy. The size of PLGA/PEI nanoparticles in phosphate-buffered saline (PBS) was about 60 nm at the optimal charge ratio. Without observable aggregation, the nanoparticles showed a better monodispersity. The PLGA-based nanoparticles were used as vector carrier for miRNA transfection in HepG2 cells. It exhibited a higher transfection efficiency and lower cytotoxicity in HepG2 cells compared to the PEI/DNA complex. The N/P ratio (ratio of the polymer nitrogen to the DNA phosphate) 6 of the PLGA/PEI/DNA nanocomplex displays the best property among various N/P proportions, yielding similar transfection efficiency when compared to Lipofectamine/DNA lipoplexes. Moreover, nanocomplex shows better serum compatibility than commercial liposome. PLGA nanocomplexes obviously accumulate in tumor cells after transfection, which indicate that the complexes contribute to cellular uptake of pDNA and pronouncedly enhance the treatment effect of miR-26a by inducing cell cycle arrest. Therefore, these results demonstrate that PLGA/PEI nanoparticles are promising non-viral vectors for gene delivery

Self-Evolution Learning for Mixup: Enhance Data Augmentation on Few-Shot Text Classification Tasks

Text classification tasks often encounter few shot scenarios with limited labeled data, and addressing data scarcity is crucial. Data augmentation with mixup has shown to be effective on various text classification tasks. However, most of the mixup methods do not consider the varying degree of learning difficulty in different stages of training and generate new samples with one hot labels, resulting in the model over confidence. In this paper, we propose a self evolution learning (SE) based mixup approach for data augmentation in text classification, which can generate more adaptive and model friendly pesudo samples for the model training. SE focuses on the variation of the model's learning ability. To alleviate the model confidence, we introduce a novel instance specific label smoothing approach, which linearly interpolates the model's output and one hot labels of the original samples to generate new soft for label mixing up. Through experimental analysis, in addition to improving classification accuracy, we demonstrate that SE also enhances the model's generalize ability

High platelet reactivity affects the clinical outcomes of patients undergoing percutaneous coronary intervention

Receiver-operating characteristic curve predicting stent thrombosis. (TIFF 5134 kb

Harnessing high-dimensional hyperentanglement through a biphoton frequency comb

Quantum entanglement is a fundamental resource for secure information processing and communications, where hyperentanglement or high-dimensional entanglement has been separately proposed towards high data capacity and error resilience. The continuous-variable nature of the energy-time entanglement makes it an ideal candidate for efficient high-dimensional coding with minimal limitations. Here we demonstrate the first simultaneous high-dimensional hyperentanglement using a biphoton frequency comb to harness the full potential in both energy and time domain. The long-postulated Hong-Ou-Mandel quantum revival is exhibited, with up to 19 time-bins, 96.5% visibilities. We further witness the high-dimensional energy-time entanglement through Franson revivals, which is observed periodically at integer time-bins, with 97.8% visibility. This qudit state is observed to simultaneously violate the generalized Bell inequality by up to 10.95 deviations while observing recurrent Clauser-Horne-Shimony-Holt S-parameters up to 2.76. Our biphoton frequency comb provides a platform in photon-efficient quantum communications towards the ultimate channel capacity through energy-time-polarization high-dimensional encoding

A study of the fire smoke propagation in subway station under the effect of piston wind

A running traffic train induces piston wind in the subway. The influence of piston wind on fire smoke propagation in subway is investigated numerically. The flow field structure in fire platform, temperature contours and velocity profiles at certain positions are obtained at various scenarios respectively. Three methods are adopted to reduce the impact of piston wind on smoke layers. Results show that large-scale vortexes and tremendous horizontal inertial force would be produced under the influence of piston wind; and that smoke stratification would be broken totally under its influence, therefore toxic gas would spread to subway hall through stairs. So the former smoke management system in a subway station becomes less effective. Results also show that combination of enhanced the volume flux of pressurization at the subway hall and lowering the height of smoke screens around stairs are necessary to restrict hazard smoke on the floor on fire. The bypass wind tunnel and ventilation shaft are useful to attenuate the magnitude of piston wind

Near-infrared Hong-Ou-Mandel interference on a silicon quantum photonic circuit

Near-infrared Hong-Ou-Mandel quantum interference is observed in silicon nanophotonic directional couplers with raw visibilities on-chip at 90.5%. Spectrally-bright 1557-nm two-photon states are generated in a periodically-poled KTiOPO4 waveguide chip, serving as the entangled photon source and pumped with a self-injection locked laser, for the photon statistical measurements. Efficient four-port coupling in the communications C-band and in the high-index-contrast silicon photonics platform is demonstrated, with matching theoretical predictions of the quantum interference visibility. Constituents for the residual quantum visibility imperfection are examined, supported with theoretical analysis of the sequentially-triggered multipair biphoton contribution and techniques for visibility compensation, towards scalable high-bitrate quantum information processing and communications.Comment: 15 pages, 6 figure

Optimizing regional cropping systems with a dynamic adaptation strategy for water sustainable agriculture in the Hebei Plain

Unsustainable overexploitation of groundwater for agricultural irrigation has led to rapid groundwater depletion and severe environmental damage in the semi-arid Hebei Plain of China. Field experiments have recommended annual winter fallowing (i.e., forgoing winter wheat production) as the most effective way to replenish groundwater. However, adopting the recommendation across the Hebei Plain would lead to a significant reduction in total wheat production. This research aims to find the most favorable water-sustainable cropping systems for different localities in the Hebei Plain, which at the regional aggregation level maintains the uppermost overall levels of wheat and grain production respectively. Our simulations indicate that in the Hebei Plain, an optimal allocation of a wheat-early maize relay intercropping system and an early maize-winter fallow cropping system across the Hebei Plain could lead to significant water savings while minimizing grain production losses to around 11%. Compared to the prevailing wheat and summer maize cropping system, to prevent a drop in the water table, 39% of the current wheat cropping land would need to be fallowed in winter, reducing irrigation water use by 2639×106m^3. Replacing the prevailing wheat and summer maize cropping system with our optimized allocation system could lead to a 36% increase in total maize production and 39% decrease in total wheat production, resulting in total agricultural irrigation water savings of 2322×106m^3 and a total grain production reduction by 11%. The findings indicate the potential benefits of our cropping system adaptation method to meet the challenge of recovering local groundwater level with the least possible reduction of wheat and total grain production in the Hebei Plain