Mid-Holocene Northern Hemisphere warming driven by Arctic amplification.

The Holocene thermal maximum was characterized by strong summer solar heating that substantially increased the summertime temperature relative to preindustrial climate. However, the summer warming was compensated by weaker winter insolation, and the annual mean temperature of the Holocene thermal maximum remains ambiguous. Using multimodel mid-Holocene simulations, we show that the annual mean Northern Hemisphere temperature is strongly correlated with the degree of Arctic amplification and sea ice loss. Additional model experiments show that the summer Arctic sea ice loss persists into winter and increases the mid- and high-latitude temperatures. These results are evaluated against four proxy datasets to verify that the annual mean northern high-latitude temperature during the mid-Holocene was warmer than the preindustrial climate, because of the seasonally rectified temperature increase driven by the Arctic amplification. This study offers a resolution to the "Holocene temperature conundrum", a well-known discrepancy between paleo-proxies and climate model simulations of Holocene thermal maximum

The impact of Arctic sea ice loss on mid-Holocene climate.

Mid-Holocene climate was characterized by strong summer solar heating that decreased Arctic sea ice cover. Motivated by recent studies identifying Arctic sea ice loss as a key driver of future climate change, we separate the influences of Arctic sea ice loss on mid-Holocene climate. By performing idealized climate model perturbation experiments, we show that Arctic sea ice loss causes zonally asymmetric surface temperature responses especially in winter: sea ice loss warms North America and the North Pacific, which would otherwise be much colder due to weaker winter insolation. In contrast, over East Asia, sea ice loss slightly decreases the temperature in early winter. These temperature responses are associated with the weakening of mid-high latitude westerlies and polar stratospheric warming. Sea ice loss also weakens the Atlantic meridional overturning circulation, although this weakening signal diminishes after 150-200 years of model integration. These results suggest that mid-Holocene climate changes should be interpreted in terms of both Arctic sea ice cover and insolation forcing

Joint Design of Digital and Analog Processing for Downlink C-RAN with Large-Scale Antenna Arrays

In millimeter-wave communication systems with large-scale antenna arrays, conventional digital beamforming may not be cost-effective. A promising solution is the implementation of hybrid beamforming techniques, which consist of low-dimensional digital beamforming followed by analog radio frequency (RF) beamforming. This work studies the optimization of hybrid beamforming in the context of a cloud radio access network (C-RAN) architecture. In a C-RAN system, digital baseband signal processing functionalities are migrated from remote radio heads (RRHs) to a baseband processing unit (BBU) in the "cloud" by means of finite-capacity fronthaul links. Specifically, this work tackles the problem of jointly optimizing digital beamforming and fronthaul quantization strategies at the BBU, as well as RF beamforming at the RRHs, with the goal of maximizing the weighted downlink sum-rate. Fronthaul capacity and per-RRH power constraints are enforced along with constant modulus constraints on the RF beamforming matrices. An iterative algorithm is proposed that is based on successive convex approximation and on the relaxation of the constant modulus constraint. The effectiveness of the proposed scheme is validated by numerical simulation results

Learning Optimal Fronthauling and Decentralized Edge Computation in Fog Radio Access Networks

Fog radio access networks (F-RANs), which consist of a cloud and multiple edge nodes (ENs) connected via fronthaul links, have been regarded as promising network architectures. The F-RAN entails a joint optimization of cloud and edge computing as well as fronthaul interactions, which is challenging for traditional optimization techniques. This paper proposes a Cloud-Enabled Cooperation-Inspired Learning (CECIL) framework, a structural deep learning mechanism for handling a generic F-RAN optimization problem. The proposed solution mimics cloud-aided cooperative optimization policies by including centralized computing at the cloud, distributed decision at the ENs, and their uplink-downlink fronthaul interactions. A group of deep neural networks (DNNs) are employed for characterizing computations of the cloud and ENs. The forwardpass of the DNNs is carefully designed such that the impacts of the practical fronthaul links, such as channel noise and signling overheads, can be included in a training step. As a result, operations of the cloud and ENs can be jointly trained in an end-to-end manner, whereas their real-time inferences are carried out in a decentralized manner by means of the fronthaul coordination. To facilitate fronthaul cooperation among multiple ENs, the optimal fronthaul multiple access schemes are designed. Training algorithms robust to practical fronthaul impairments are also presented. Numerical results validate the effectiveness of the proposed approaches.Comment: to appear in IEEE Transactions on Wireless Communication

Learning Robust Beamforming for MISO Downlink Systems

This paper investigates a learning solution for robust beamforming optimization in downlink multi-user systems. A base station (BS) identifies efficient multi-antenna transmission strategies only with imperfect channel state information (CSI) and its stochastic features. To this end, we propose a robust training algorithm where a deep neural network (DNN), which only accepts estimates and statistical knowledge of the perfect CSI, is optimized to fit to real-world propagation environment. Consequently, the trained DNN can provide efficient robust beamforming solutions based only on imperfect observations of the actual CSI. Numerical results validate the advantages of the proposed learning approach compared to conventional schemes.Comment: to appear in IEEE Communications Letters (5 pages, 5 figures, 1 tables

Large-Scale Plasma Polymer Coating on Heat Exchanger Fins for Improving the Wettability

This research presents the results of the recently developed large-scale hydrophilic polymer coating by plasma polymerization, optimum plasma zone (OPZ) process. The excellent hydrophilicity of heat exchanger fin surface could give good effects to efficient drainage of condensate water as well as heat transfer performance. The hydrophilicity of layer treated by large-scale OPZ system is excellent irrespective of line speed from 0.6 m/min to 2.4 m/min. The good lateral uniformity of the hydrophilicity could be acquired in large scale OPZ treatment. The application of OPZ technique to the heat exchanger could enhance the efficiency of heat transfer, resulting from decrease of pressure drop. Due to long-term durability of hydrophilicity, the heat transfer performance improved by OPZ process cannot be deteriorated with operation cycle

Hybrid carbon thermal interface materials for thermoelectric generator devices

Thermal interface materials (TIMs) are extensively used in electronic devices as efficient heat transfer materials. We fabricated all-carbon TIMs by hybridizing single-wall carbon nanotubes (SWCNTs) with graphite and demonstrated their performance by applying them to a thermoelectric generator (TEG) device. The hybrid carbon TIM exhibited maximum thermal conductivity when the SWCNT content was near 10 wt%. The TIM thermal contact resistance measured by a home-made calorimeter setup was 2.19 × 10−4m2K/W, which did not vary with temperature but decreased with applied pressure. Post-treatment of the TIM with a silane coupling agent further reduced the TIM thermal contact resistance by 30%. When the TIM was placed between a TEG device and a copper heat reservoir, the TEG output power increased with the temperature difference across the TEG and applied pressure. Moreover, the post-treatment of the TIM enhanced the output power of the TEG device by up to 18.5%. This work provides a simple and effective pathway towards a carbon-based TIM that can be applied to a high temperature TEG. © 2020, The Author(s).1