Scalability and flexibility are widely considered as two major design goals for 5G networks. Aiming at these goals, this article first identifies a promising architecture based on the heterogeneous ...cloud radio access network (H-CRAN), reviews the challenges in MIMO precoding for H-CRAN, and then proposes a scalable and flexible massive MIMO precoding scheme by exploiting the null-space of user signals. Specifically, the system can accomplish effective radio resource management and flexible spatial coordination by distinguishing the intended and victim users' CSI, and avoid the interference by precoding within the null-space for the CSI of victim users. Simulation results indicate that the proposed scheme is capable to effectively alleviate the interference to victim users and support high QoS as well as spectral efficiency.
Tracking Retail Investor Activity BOEHMER, EKKEHART; JONES, CHARLES M.; ZHANG, XIAOYAN ...
The Journal of finance (New York),
October 2021, Letnik:
76, Številka:
5
Journal Article
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ABSTRACT
We provide an easy method to identify marketable retail purchases and sales using recent, publicly available U.S. equity transactions data. Individual stocks with net buying by retail ...investors outperform stocks with negative imbalances by approximately 10 bps over the following week. Less than half of the predictive power of marketable retail order imbalance is attributable to order flow persistence, while the rest cannot be explained by contrarian trading (proxy for liquidity provision) or public news sentiment. There is suggestive, but only suggestive, evidence that retail marketable orders might contain firm‐level information that is not yet incorporated into prices.
O bjective: In this paper, we introduce an autonomous robotic ultrasound (US) imaging system based on reinforcement learning (RL). The proposed system and framework are committed to controlling the ...US probe to perform fully autonomous imaging of a soft, moving and marker-less target based only on single RGB images of the scene. Methods: We propose several different approaches and methods to achieve the following objectives: real-time US probe controlling, soft surface constant force tracking and automatic imaging. First, to express the state of the robotic US imaging task, we proposed a state representation model to reduce the dimensionality of the imaging state and encode the force and US information into the scene image space. Then, an RL agent is trained by a policy gradient theorem based RL model with the single RGB image as the only observation. To achieve adaptable constant force tracking between the US probe and the soft moving target, we propose a force-to-displacement control method based on an admittance controller. Results: In the simulation experiment, we verified the feasibility of the integrated method. Furthermore, we evaluated the proposed force-to-displacement method to demonstrate the safety and effectiveness of adaptable constant force tracking. Finally, we conducted phantom and volunteer experiments to verify the feasibility of the method on a real system. Conclusion: The experiments indicated that our approaches were stable and feasible in the autonomic and accurate control of the US probe. Significance: The proposed system has potential application value in the image-guided surgery and robotic surgery.
This study investigated the role of bromide ions in the degradation of nine pharmaceuticals and personal care products (PPCPs) during the UV/chlorine treatment of simulated drinking water containing ...2.5 mgC L−1 natural organic matter (NOM). The kinetics of contributions from UV irradiation and from oxidation by free chlorine, free bromine, hydroxyl radical and reactive halogen species were evaluated. The observed loss rate constants of PPCPs in the presence of 10 μM bromide were 1.6–23 times of those observed in the absence of bromide (except for iopromide and ibuprofen). Bromide was shown to play multiple roles in PPCP degradation. It reacts rapidly with free chlorine to produce a trace amount of free bromine, which then contributes to up to 55% of the degradation of some PPCPs during 15 min of UV/chlorine treatment. Bromide was also shown to reduce the level of HO• and to change the reactive chlorine species to bromine-containing species, which resulted in decreases in ibuprofen degradation and enhancement in carbamazepine and caffeine degradation, respectively. Reactive halogen species contributed to between 37 and 96% of the degradation of the studied PPCPs except ibuprofen in the presence of 10 μM bromide ion. The effect of bromide is non-negligible during the UV/chlorine treatment.
Cellular vehicle-to-everything (V2X) communication is crucial to support future diverse vehicular applications. However, for safety-critical applications, unstable vehicle-to-vehicle (V2V) links, and ...high signaling overhead of centralized resource allocation approaches become bottlenecks. In this article, we investigate a joint optimization problem of transmission mode selection and resource allocation for cellular V2X communications. In particular, the problem is formulated as a Markov decision process, and a deep reinforcement learning (DRL)-based decentralized algorithm is proposed to maximize the sum capacity of vehicle-to-infrastructure users while meeting the latency and reliability requirements of V2V pairs. Moreover, considering training limitation of local DRL models, a two-timescale federated DRL algorithm is developed to help obtain robust models. Wherein, the graph theory-based vehicle clustering algorithm is executed on a large timescale and in turn, the federated learning algorithm is conducted on a small timescale. The simulation results show that the proposed DRL-based algorithm outperforms other decentralized baselines, and validate the superiority of the two-timescale federated DRL algorithm for newly activated V2V pairs.
Microcystin-LR (MC-LR), a toxin produced by cyanobacteria, is very toxic and poses a threat to public health when entering water treatment works. In this study, UV/chlorine process, as an advanced ...oxidation process (AOP), has been demonstrated for effective elimination of MC-LR levels and associated toxicity. At a chlorine dose of 3.0 mg L−1 and UV fluence of 125 mJ cm−2, MC-LR (initial concentration 1.0 μM) was reduced by 92.5%, which was much higher than 20.3% removal under UV irradiation alone and 65.1% removal during dark chlorination. Enhanced degradation was attributed by hydroxyl radicals (HO) and reactive chlorine species (RCS), mainly Cl2- and ClO. Increasing chlorine doses or lowering pH favored MC-LR removal. Increased bicarbonate and natural organic matter concentrations inhibited MC-LR removal, but bromide ions enhanced MC-LR removal instead. MC-LR elimination rates in natural waters were roughly two times smaller than those in ultrapure water. The reactive radicals promoted hydroxylation of both diene of Adda moiety and double bond of Mdha moiety in MC-LR. UV exposure enhanced the dechlorination of chloro-MC-LR via the cleavage of CCl bond. The toxicity was evaluated by a protein phosphatase (PP2A) inhibition assay. At a chlorine dose of 3.0 mg L−1 and UV fluence of 125 mJ cm−2, the toxicity of the treated water was reduced by 75.0%, which was also higher than 25.7% and 46.7% removal under UV irradiation alone and during dark chlorination, respectively. These results highlight UV/chlorine is an efficient AOP for MC-LR degradation and detoxification.
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•UV254 irradiation combined with chlorine exhibits synergic effects on MC-LR degradation.•MC-LR degradation rate was inhibited by NOM and HCO3−; but accelerated by Br−.•MC-LR degradation mechanisms and products were proposed.•Reactive radicals (HO.•, Cl2•-, and ClO•) contributed to MC-LR degradation.
Robotic ultrasound systems (RUS) have gained increasing attention because they can automate repetitive procedures and relieve operators' workloads. However, the complexity and uncertainty of the ...human surface pose a challenge for stable scanning control. This paper proposes a general active compliance control strategy based on inverse reinforcement learning (IRL) to perform adaptable scanning for uncertain and unstructured environments. We analyze the manual scanning process pattern and propose a velocity-and-force-related control strategy to achieve variable force control and handle unpredictable deformation. Then, a hybrid policy optimization framework is proposed to improve transferability. In this framework, a reinforcement learning (RL) policy with a predefined reward is built to establish the relationship between contact force and posture. Furthermore, the policy is re-optimized using IRL and generated demonstrations for IRL training. The policy is trained on simple standard phantoms and further evaluated for stability and transferability in unseen and complex environments. Quantitative results show that the difference between the proposed method and the 3-D reconstructed model in terms of posture is (2.3±1.3°, 1.9±1.2°) in continuous scans. Overall, our method provides a solution for improving the usability of robotic ultrasound systems in real-world environments.
The integration of luminescence and chirality in easy-scalable metal-organic frameworks gives rise to the development of advanced luminescent sensors. To date, the synthesis of chiral metal-organic ...frameworks is poorly predictable and their chirality primarily originates from components that constitute the frameworks. By contrast, the introduction of chirality into the pores of metal-organic frameworks has not been explored to the best of our knowledge. Here, we demonstrate that chirality can be introduced into an anionic Zn-based metal-organic framework via simple cation exchange, yielding dual luminescent centers comprised of the ligand and Tb
ions, accompanied by a chiral center in the pores. This bifunctional material shows enantioselectivity luminescent sensing for a mixture of stereoisomers, demonstrated for Cinchonine and Cinchonidine epimers and amino alcohol enantiomers, from which the quantitative determination of the stereoisomeric excess has been obtained. This study paves a pathway for the design of multifunctional metal-organic framework systems as a useful method for rapid sensing of chiral molecules.
By using a Gaussian process prior and a location-scale mixture representation of the asymmetric Laplace distribution, we develop a Bayesian analysis for the composite quantile single-index regression ...model. The posterior distributions for the unknown parameters are derived, and the Markov chain Monte Carlo sampling algorithms are also given. The proposed method is illustrated by three simulation examples and a real dataset.
The finite element numerical simulation results of deep pit deformation are greatly influenced by soil layer parameters, which are crucial in determining the accuracy of deformation prediction ...results. This study employs the orthogonal experimental design to determine the combinations of various soil layer parameters in deep pits. Displacement values at specific measurement points were calculated using PLAXIS 3D under these varying parameter combinations to generate training samples. The nonlinear mapping ability of the Back Propagation (BP) neural network and Particle Swarm Optimization (PSO) were used for sample global optimization. Combining these with actual onsite measurements, we inversely calculate soil layer parameter values to update the input parameters for PLAXIS 3D. This allows us to conduct dynamic deformation prediction studies throughout the entire excavation process of deep pits. The results indicate that the use of the PSO-BP neural network for inverting soil layer parameters effectively enhances the convergence speed of the BP neural network model and avoids the issue of easily falling into local optimal solutions. The use of PLAXIS 3D to simulate the excavation process of the pit accurately reflects the dynamic changes in the displacement of the retaining structure, and the numerical simulation results show good agreement with the measured values. By updating the model parameters in real-time and calculating the pile displacement under different working conditions, the absolute errors between the measured and simulated values of pile top vertical displacement and pile body maximum horizontal displacement can be effectively reduced. This suggests that inverting soil layer parameters using measured values from working conditions is a feasible method for dynamically predicting the excavation process of the pit. The research results have some reference value for the selection of soil layer parameters in similar areas.
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