40 research outputs found
HybridNet: Dual-Branch Fusion of Geometrical and Topological Views for VLSI Congestion Prediction
Accurate early congestion prediction can prevent unpleasant surprises at the
routing stage, playing a crucial character in assisting designers to iterate
faster in VLSI design cycles. In this paper, we introduce a novel strategy to
fully incorporate topological and geometrical features of circuits by making
several key designs in our network architecture. To be more specific, we
construct two individual graphs (geometry-graph, topology-graph) with distinct
edge construction schemes according to their unique properties. We then propose
a dual-branch network with different encoder layers in each pathway and
aggregate representations with a sophisticated fusion strategy. Our network,
named HybridNet, not only provides a simple yet effective way to capture the
geometric interactions of cells, but also preserves the original topological
relationships in the netlist. Experimental results on the ISPD2015 benchmarks
show that we achieve an improvement of 10.9% compared to previous methods
Coordinating a Supply Chain with a Loss-Averse Retailer under Yield and Demand Uncertainties
This paper investigates the channel coordination of a supply chain (SC) consisting of a loss-averse retailer and a risk-neutral supplier under yield and demand uncertainties. Three existing contracts are analyzed. Our results demonstrate that the buyback (BB) and quantity flexibility (QF) contracts can not only coordinate the supply chain but also lead to Pareto improvement for each player, while the wholesale price (WP) contract fails to coordinate the chain due to the effects of double marginalization and risk preference. For comparison, a chain with a risk-neutral retailer is also analyzed. Furthermore, numerical examples are provided to demonstrate the effectiveness of the coordination contracts, and the impacts of loss aversion and random yield on the decision-making behaviors and system performance are then discussed
Highly specular carbon nanotube absorbers
© 2010 American Institute of Physics. The electronic version of this article is the complete one and can be found at: http://dx.doi.org/10.1063/1.3502597DOI: 10.1063/1.3502597Specular black materials have important applications, such as in absolute cryogenic radiometers, space-borne spectroradiometers, and some energy conversion devices. While vertically aligned carbon nanotubes (VACNT) can have close-to-unity absorptance, so far the reported reflection has been essentially diffuse. This letter describes a highly specular black absorber made of VACNT. Both the bidirectional reflectance distribution function and specular reflectance were measured at the wavelength λ = 635 nm using a laser scatterometer. The ordinary and extraordinary optical constants were obtained by fitting the specular reflectance, calculated from modified reflectance formulae for light incident from air to a uniaxial medium, considering surface roughness. Furthermore, the absorptance at λ = 635 nm was shown to be 0.994±0.002, based on the measured directional-hemispherical reflectance
Highly Strong, Tough, and Cryogenically Adaptive Hydrogel Ionic Conductors via Coordination Interactions
Despite the promise of high flexibility and conformability of hydrogel ionic conductors, existing polymeric conductive hydrogels have long suffered from compromises in mechanical, electrical, and cryoadaptive properties due to monotonous functional improvement strategies, leading to lingering challenges. Here, we propose an all-in-one strategy for the preparation of poly(acrylic acid)/cellulose (PAA/Cel) hydrogel ionic conductors in a facile yet effective manner combining acrylic acid and salt-dissolved cellulose, in which abundant zinc ions simultaneously form strong coordination interactions with the two polymers, while free solute salts contribute to ionic conductivity and bind water molecules to prevent freezing. Therefore, the developed PAA/Cel hydrogel simultaneously achieved excellent mechanical, conductive, and cryogenically adaptive properties, with performances of 42.5 MPa for compressive strength, 1.6 MPa for tensile strength, 896.9% for stretchability, 9.2 MJ m−3 for toughness, 59.5 kJ m−2 for fracture energy, and 13.9 and 6.2 mS cm−1 for ionic conductivity at 25 and −70 °C, respectively. Enabled by these features, the resultant hydrogel ionic conductor is further demonstrated to be assembled as a self-powered electronic skin (e-skin) with high signal-to-noise ratio for use in monitoring movement and physiological signals regardless of cold temperatures, with hinting that could go beyond high-performance hydrogel ionic conductors
Sea Surface Skin Temperature Retrieval from FY-3C/VIRR
The visible and infrared scanning radiometer (VIRR) onboard the Fengyun-3C (FY-3C) meteorological satellite has 11 μm and 12 μm channels, which are capable of sea surface temperature (SST) observations. This study is based on atmospheric radiative transfer modeling (RTM) by applying Bayesian cloud detection theory and optimal estimation (OE) to obtain sea surface skin temperature (SSTskin) from VIRR in the Northwest Pacific. The inter-calibration of FY-3C/VIRR 11 μm and 12 μm brightness temperature (BT) is carried out using the Moderate Resolution Imaging Spectroradiometer (MODIS) as the reference sensor. Bayesian cloud detection and OE SST retrieval with the calibration BT data is performed to obtain SSTskin. The SSTskin retrievals are compared with the buoy SST with a temporal window of 1 h and a spatial window of 0.01°. The bias is −0.12 °C, and the standard deviation is 0.52 °C. Comparisons of the retrieved SSTskin with the AVHRR (Advanced Very High Resolution Radiometer) SSTskin from European Space Agency Sea Surface Temperature Climate Change Initiative (ESA SST CCI) project show the bias of 0.08 °C and the standard deviation of 0.55 °C. The results indicate that the VIRR SSTskin are consistent with AVHRR SSTskin and buoy SST
Sea Surface Skin Temperature Retrieval from FY-3C/VIRR
The visible and infrared scanning radiometer (VIRR) onboard the Fengyun-3C (FY-3C) meteorological satellite has 11 μm and 12 μm channels, which are capable of sea surface temperature (SST) observations. This study is based on atmospheric radiative transfer modeling (RTM) by applying Bayesian cloud detection theory and optimal estimation (OE) to obtain sea surface skin temperature (SSTskin) from VIRR in the Northwest Pacific. The inter-calibration of FY-3C/VIRR 11 μm and 12 μm brightness temperature (BT) is carried out using the Moderate Resolution Imaging Spectroradiometer (MODIS) as the reference sensor. Bayesian cloud detection and OE SST retrieval with the calibration BT data is performed to obtain SSTskin. The SSTskin retrievals are compared with the buoy SST with a temporal window of 1 h and a spatial window of 0.01°. The bias is −0.12 °C, and the standard deviation is 0.52 °C. Comparisons of the retrieved SSTskin with the AVHRR (Advanced Very High Resolution Radiometer) SSTskin from European Space Agency Sea Surface Temperature Climate Change Initiative (ESA SST CCI) project show the bias of 0.08 °C and the standard deviation of 0.55 °C. The results indicate that the VIRR SSTskin are consistent with AVHRR SSTskin and buoy SST
Spirocyclizative Remote Arylcarboxylation of Non-Activated Arenes with CO2 via Visible-Light-Induced Reductive Dearomatization
Visible-light-induced reductive dearomatization of
non-activated arenes is a very challenging transformation and remains in its
infancy. Herein, we report a novel strategy to achieve a visible-light-induced
spirocyclizative remote arylcarboxylation of non-activated arenes including
naphthalenyl- and phenyl-bearing aromatics with CO2 under mild
conditions through a radical-polar crossover cascade (RPCC). This reductive
dearomatization protocol rapidly delivers a broad range of spirocyclic and
valuable carboxylic acid derivatives from readily accessible aromatic
precursors with generally good regioselectivity and chemoselectivity