胶东一体化背景下天然气发展策略研究

大力发展天然气对于促进能源结构优化调整和大气污染防治具有重要意义,是实现"碳达峰""碳中和"的重要路径.借力胶东一体化发展战略的提出,引领胶东五市天然气基础设施协同发展,促进胶东一体化战略在能源领域的实施.     

Ni-Foam Structured Ni-Phyllosilicate Ensemble as an Efficient Monolithic Catalyst for CO2 Methanation

This work proposed a new path to synthesize Ni-phyllosilicate through the reaction of nickel hydroxide and silica sol on the surface of Ni-foam to form the monolithic Ni-phyllosilicate/Ni-foam catalyst. Ni-phyllosilicate could reprint the morphology of nickel hydroxid and firmly anchor on the framework of Ni-foam, which obtained fine Ni particles of 2.8 nm after reduction in H₂ at 650 °C, resulting in high catalytic activity for CO₂ methanation. In addition, the Ni-phyllosilicate/Ni-foam catalyst showed high long-term stability in a 100 h-lifetime test owing to the combined effects of surface confinement of Ni-phyllosilicate, firm anchoring between Ni-phyllosilicate and Ni-foam, as well as the high heat transfer property of Ni-foam.

Graphical Abstract

     

Omega-6支撑身体，Omega-3支撑大脑：均衡摄入对儿童大脑发育的影响（网络首发、推荐阅读）

人体大脑和身体的发育，需要从食物中摄取均衡的营养物质。人类大脑是区分人类和其他动物的特征。食物中的必需脂肪酸是机体组织结构和功能的必要组成部分。Omega-6（O6）亚油酸（LA6）是皮肤组织的组成成分，且是炎症、血栓形成、免疫和其他信号分子的前体；Omega-3（O3）α-亚麻酸（ALA3），特别是其长链代谢产物——二十二碳六烯酸（DHA3），是大脑、视网膜和部分神经组织中的关键组分。从富含LA6脂肪酸（缺乏O3脂肪酸）的植物籽中提取出的廉价而优质油脂，是20世纪的西方国家食品工业生产的主要脂肪来源。在代谢通路中，高浓度的LA6脂肪酸可拮抗O3脂肪酸代谢，造成O3脂肪酸不足，因此，在给怀孕动物的饲料中，只提供富含LA6但缺乏O3脂肪酸的油脂作为唯一的脂肪来源，会导致幼崽大脑发育不良。过去20~30年的研究表明，低含量LA6且含DHA3的油脂可改善大脑的功能。近年来的研究较多集中在营养因素对大脑发育的影响，最新研究数据表明，脂肪酸平衡对营养不良儿童的大脑发育尤为重要。世界卫生组织（WHO）越来越重视大脑的营养健康，通过其下属的食品法典委员会，建议用于治疗严重急性营养不良儿童的即食治疗食品中，使用含有均衡脂肪酸组成/构成的脂肪。同样，脂肪酸均衡对老年人可能也很重要。目前，业界已经有了调整油脂成分的方法，以确保脂肪酸均衡，从而维持人体整个生命周期的大脑健康。     

An automated treatment planning strategy for highly noncoplanar radiotherapy arc trajectories

Radiation therapy is a technology-driven cancer treatment modality that has experienced significant advances over the last decades, due to multidisciplinary contributions that include engineering and computing. Recent technological developments allow the use of noncoplanar volumetric modulated arc therapy (VMAT), one of the most recent photon treatment techniques, in clinical practice. In this work, an automated noncoplanar arc trajectory optimization framework designed in two modular phases is presented. First, a noncoplanar beam angle optimization algorithm is used to obtain a set of noncoplanar irradiation directions. Then, anchored in these directions, an optimization strategy is proposed to compute an optimal arc trajectory. The computational experiments considered a pool of twelve difficult head-and-neck tumor cases. It was possible to observe that, for some of these cases, the optimized noncoplanar arc trajectories led to significant treatment planning quality improvements, when compared with coplanar VMAT treatment plans. Although these experiments were done in a research environment treatment planning software (matRad), the conclusions can be of interest for a clinical setting: automated procedures can simplify the current treatment workflow, produce high-quality treatment plans, making better use of human resources and allowing for unbiased comparisons between different treatment techniques.     

Revisiting the Parallel Strategy for DOACROSS Loops

Journal of Computer Science and Technology - DOACROSS loops are significant parts in many important scientific and engineering applications, which are generally exploited pipeline/wave-front...     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

RLPAS: Reinforcement Learning-based Proactive Auto-Scaler for Resource Provisioning in Cloud Environment

Mobile Networks and Applications - Public cloud system offers Infrastructure-as-a-Service (IaaS) to deliver the computational resources on demand. Resource requirements of a cloud environment are...     

Hierarchical Attention for Part-Aware Face Detection

International Journal of Computer Vision - Expressive representations for characterizing face appearances are essential for accurate face detection. Due to different poses, scales, illumination,...     

Spreading and Curing Behaviors of a Thermosetting Droplet-Silicone on a Heated Surface

Thermosetting materials are widely used as encapsulation in the electrical packaging to protect the core electronic components from external force, moisture, dust, and other factors. However, the spreading and curing behaviors of such kind of fluid on a heated surface have been rarely explored. In this study, we experimentally and numerically investigated the spreading and curing behaviors of the silicone(OE6550 A/B, which is widely used in the light-emitting diode packaging) droplet with diameter of ～2.2 mm on a heated surface with temperature ranging from 25 ℃ to 250 ℃. For the experiments, we established a setup with high-speed camera and heating unit to capture the fast spreading process of the silicone droplet on the heated surface. For the numerical simulation, we built a viscosity model of the silicone by using the Kiuna's model and combined the viscosity model with the Volume of Fluid(VOF) model by the User Defined Function(UDF) method. The results show that the surface temperature significantly affected the spreading behaviors of the silicone droplet since it determines the temperature and viscosity distribution inside the droplet. For surface temperature varied from 25 ℃ to 250 ℃, the final contact radius changed from ～2.95 mm to ～1.78 mm and the total spreading time changed from ～511 s to ～0.15 s. By further analyzing the viscosity evolution of the droplet, we found that the decreasing of the total spreading time was caused by the decrease of the viscosity under high surface temperature at initial spreading stage, while the reduction of the final contact radius was caused by the curing of the precursor film. This study supplies a strategy to tuning the spreading and curing behavior of silicone by imposing high surface temperature, which is of great importance to the electronic packaging.     

Threshold privacy-preserving cloud auditing with multiple uploaders

International Journal of Information Security - Data integrity is a critical security issue in cloud storage. The data integrity checking schemes by a third-party auditor (TPA) have attracted a lot...