1,731 research outputs found
Collaborative Filtering with Social Exposure: A Modular Approach to Social Recommendation
This paper is concerned with how to make efficient use of social information
to improve recommendations. Most existing social recommender systems assume
people share similar preferences with their social friends. Which, however, may
not hold true due to various motivations of making online friends and dynamics
of online social networks. Inspired by recent causal process based
recommendations that first model user exposures towards items and then use
these exposures to guide rating prediction, we utilize social information to
capture user exposures rather than user preferences. We assume that people get
information of products from their online friends and they do not have to share
similar preferences, which is less restrictive and seems closer to reality.
Under this new assumption, in this paper, we present a novel recommendation
approach (named SERec) to integrate social exposure into collaborative
filtering. We propose two methods to implement SERec, namely social
regularization and social boosting, each with different ways to construct
social exposures. Experiments on four real-world datasets demonstrate that our
methods outperform the state-of-the-art methods on top-N recommendations.
Further study compares the robustness and scalability of the two proposed
methods.Comment: Accepted for publication at the 32nd Conference on Artificial
Intelligence (AAAI 2018), New Orleans, Louisian
Cardioprotective effects of Dan-Yang-Fu-Xin decoction on chronic heart failure in rats
Purpose: To evaluate the cardioprotective effects and possible mechanisms of Dan-Yang-Fu-Xin decoction (DYFX) in a rat chronic heart failure (CHF).Methods: A CHF rat model induced by ligation of the left anterior descending coronary artery was used to investigate the cardioprotective effects of DYFX. After intragastric administration for 8 weeks, several functional cardiac indices, including fractional shortening (FS), ejection fraction (EF), heart rate (HR) and cardiac output (CO) were assessed by ultrasound examination. Subsequently, inflammatory markers, viz, interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α), myocardial enzymes, namely, lactate dehydrogenase (LDH) and creatine kinase (CK), were also assessed by enzyme-linked immunosorbent assay (ELISA).Results: Intragastric administration of DYFX (200, 400 and 600 mg/kg) significantly reversed the decrease in body weight and increase in cardiac weight (p < 0.05) induced by CHF. Treatment with DYFX also significantly reversed EF, FS, HR, and CO changes in CHF rats. In addition, DYFX inhibited the two inflammatory cytokines (TNF-α and IL-6) and myocardial enzymes (CK and LDH), suggesting that these effects may include the mechanisms of cardioprotectiion involved in attenuation of CHF.Conclusion: DYFX possesses cardioprotective effects involving CHF. The protective mechanisms may include the suppression of expression of inflammatory mediators and myocardial enzymes.Keywords: Dan-Yang-Fu-Xin decoction, Cardioprotection, Chronic heart failure, Inflammatory mediators, Myocardial enzyme
Interfacial thermal conductance in graphene/black phosphorus heterogeneous structures
Graphene, as a passivation layer, can be used to protect the black phosphorus
from the chemical reaction with surrounding oxygen and water. However, black
phosphorus and graphene heterostructures have low efficiency of heat
dissipation due to its intrinsic high thermal resistance at the interfaces. The
accumulated energy from Joule heat has to be removed efficiently to avoid the
malfunction of the devices. Therefore, it is of significance to investigate the
interfacial thermal dissipation properties and manipulate the properties by
interfacial engineering on demand. In this work, the interfacial thermal
conductance between few-layer black phosphorus and graphene is studied
extensively using molecular dynamics simulations. Two critical parameters, the
critical power Pcr to maintain thermal stability and the maximum heat power
density Pmax with which the system can be loaded, are identified. Our results
show that interfacial thermal conductance can be effectively tuned in a wide
range with external strains and interracial defects. The compressive strain can
enhance the interfacial thermal conductance by one order of magnitude, while
interface defects give a two-fold increase. These findings could provide
guidelines in heat dissipation and interfacial engineering for thermal
conductance manipulation of black phosphorus-graphene heterostructure-based
devices.Comment: 33 pages, 22 figure
UAV-Assisted Relaying and Edge Computing: Scheduling and Trajectory Optimization
In this paper, we study an unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) architecture, in which a UAV roaming around the area may serve as a computing server to help user equipment (UEs) compute their tasks or act as a relay for further offloading their computation tasks to the access point (AP). We aim to minimize the weighted sum energy consumption of the UAV and UEs subject to the task constraints, the information-causality constraints, the bandwidth allocation constraints and the UAV's trajectory constraints. The required optimization is nonconvex, and an alternating optimization algorithm is proposed to jointly optimize the computation resource scheduling, bandwidth allocation, and the UAV's trajectory in an iterative fashion. The numerical results demonstrate that significant performance gain is obtained over conventional methods. Also, the advantages of the proposed algorithm are more prominent when handling computation-intensive latency-critical tasks
Effect of PulseâandâGlide Strategy on Traffic Flow for a Platoon of Mixed Automated and Manually Driven Vehicles
The fuel consumption of ground vehicles is significantly affected by how they are driven. The fuelâoptimized vehicular automation technique can improve fuel economy for the host vehicle, but their effectiveness on a platoon of vehicles is still unknown. This article studies the performance of a wellâknown fuelâoptimized vehicle automation strategy, i.e., PulseâandâGlide (PnG) operation, on traffic smoothness and fuel economy in a mixed traffic flow. The mixed traffic flow is assumed to be a singleâlane highway on flat road consisting of both driverless and manually driven vehicles. The driverless vehicles are equipped with fuel economyâoriented automated controller using the PnG strategy. The manually driven vehicles are simulated using the Intelligent Driver Models (IDM) to mimic the average carâfollowing behavior of human drivers in naturalistic traffics. A series of simulations are conducted with three scenarios, i.e., a single car, a car section, and a car platoon. The simulation results show that the PnG strategy can significantly improve the fuel economy of individual vehicles. For traffic flows, the fuel economy and traffic smoothness vary significantly under the PnG strategy.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/115907/1/mice12168.pd
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