Reduction of sidelobe levels in multicarrier radar signals via the fusion of hill patterns and geometric progression

Multi-carrier waveforms have several advantages over single-carrier waveforms for radar communication. Employing multi-carrier complementary phase-coded (MCPC) waveforms in radar applications has recently attracted significant attention. MCPC radar signals take advantage of orthogonal frequency division multiplexing properties, and several authors have explored the use of MCPC signals and the difficulties associated with their implementation. The sidelobe level and peak-to-mean-envelope-power ratio (PMEPR) are the key issues that must be addressed to improve the performance of radar signals. We propose a scheme that applies pattern-based scaling and geometric progression methods to enhance sidelobe and PMEPR levels in MCPC radar signals. Numerical results demonstrate the improvement of sidelobe and PMEPR levels in the proposed scheme. Additionally, autocorrelations are obtained and analyzed by applying the proposed scheme in extensive simulation experiments.     

Facile synthesis of black phosphorus directly grown on carbon paper as an efficient OER Electrocatalyst: Role of Interfacial charge transfer and induced local charge distribution

Black phosphorus (BP), as a new 2D material, is normally synthesized by a high-pressure and high-temperature (HPHT) method from white and red phosphorus, which severely hinders the further development of BP for any potential applications and leads to search for other potential applications of BP with big challenge. Herein, we develop a facile and efficient Thermal-Vaporization-Transformation (TVT) approach to prepare a highly active BP directly grown on carbon paper as the electrode for Oxygen evolution reaction (OER), showing a low onset potential of 1.45 V versus RHE. Simultaneously, the current density of BP-CP illustrates the excellent electro-catalysis stability only decreases by 3.4% after continuous operation for 10000 s. Meanwhile, the density functional theory (DFT) calculations further illustrates the P-doped carbon layer in the upper side of BP layer is actually responsible for its enhanced OER property, and the adjacent carbon atoms of the embedded P atoms are actually the active sites due to the induced local change distribution by intramolecular change transfer. Considering the facile, but efficient and scalable, TVT approach can directly synthesize BP-CP with excellent OER performance, which is promising for BP electrocatalysts used for OER in metal-air batteries, fuel cells, water-splitting devices, even other key renewable energy.     

Mechanical properties,corrosion resistance,and rubber pad forming of cold differential speed-rolled pure titanium for bipolar plates of proton-exchange membrane fuel cells

Due to problems such as pores on surface-treated coatings, the corrosion resistance of pure titanium bipolar plates for proton-exchange membrane fuel cells can be further improved by increasing the corrosion resistance of pure titanium by using differential speed-rolling (DSR); however, these materials have not yet reached the standard requirements of bipolar plates (corrosion current density i_corr＜10³ nA·cm^?2). In this work, the corrosion resistance of pure titanium was improved by optimizing the DSR process while the strength was maintained. The best corrosion resistance of the DSR pure titanium was achieved when the roller speed ratio was 2, while i_corr was 429 nA·cm^?2 in a solution of 0.5 M H₂SO₄ and 2 mg/L HF at room temperature. The formability of the DSR pure titanium for bipolar plates was verified. The optimal holding pressure range was 6.8–7.0 kN.     

LinkingPark: An automatic semantic table interpretation system

In this paper, we present LinkingPark, an automatic semantic annotation system for tabular data to knowledge graph matching. LinkingPark is designed as a modular framework which can handle Cell-Entity Annotation (CEA), Column-Type Annotation (CTA), and Columns-Property Annotation (CPA) altogether. It is built upon our previous SemTab 2020 system, which won the 2nd prize among 28 different teams after four rounds of evaluations. Moreover, the system is unsupervised, stand-alone, and flexible for multilingual support. Its backend offers an efficient RESTful API for programmatic access, as well as an Excel Add-in for ease of use. Users can interact with LinkingPark in near real-time, further demonstrating its efficiency.     

Validation of qPCR method for enterococci quantification at Toronto beaches: Application for rapid recreational water monitoring

Rapid quantitative PCR-based methods for enterococci monitoring can allow public health authorities to make more timely beach posting decisions. However, qPCR methods must be assessed for proposed sites as locale-specific factors may affect DNA recovery or qPCR inhibition. We assessed the feasibility of the USEPA 1609.1 qPCR-based (Enterococcus) method at two urban Toronto beaches and three recreational areas at nearby river mouths in parallel with culture-based methods on the same water samples. A strong positive correlation was observed between the Enterococcus qPCR method and culturing-based quantification methods for E. coli and enterococci at both beaches and two river mouth areas. One river, known to be highly sewage-impacted, did not yield DNA suitable for qPCR analyses. qPCR results from biological replicates were strongly correlated and showed coefficients of variation as low as or lower than culture-based methods. With respect to Beach Action Value exceedances, the USEPA 1609.1 qPCR method provided an 80–90% level of agreement with E. coli enumeration results and >90% with enterococci enumeration. Results indicated that if recreational water locations and sampling conditions met the requirements of the USEPA 1609.1 qPCR method, the method can meet or exceed all quality control requirements and provide water quality results within 3.5 h for diverse recreational water settings around the City of Toronto.     

Realizing fragment spawning and fragment growth in the parallelized Discrete Element Method (DEM) during modelling of comminution

The particle based Discrete Element Method (DEM) can be applied to examine comminution processes. In this study, a DEM framework has been extended to model particle breakage without mass loss. After a breakage event occurs, spherical particles, as often considered in the DEM, are replaced by size reduced spherical fragments. During the following time steps, the fragments grow to their desired sizes, so that the mass loss can be counterbalanced. Previously defined overlaps with adjacent unbroken and broken particles (fragments) as well as walls are allowed. The breakage model has been realized in a parallelized DEM framework because comminution processes are often attributed to large numbers of particles and by parallelization the computational time can be reduced efficiently. An oedometer (one-dimensional compression in axial direction of a confined particle bed) has been modelled to investigate the parallelization efficiency and the influence of the permitted overlaps during the growth process on the growth duration. A simplified roller mill has been considered to examine the applicability of the breakage procedure considering parallelization. The results show that parallelization reduces computational time considerably. The breakage procedure is suitable to model comminution processes involving even densely packed particle systems and is superior to existing approaches.     

基于儿童使用主体的建成环境评价尺度研究

评价尺度是建筑使用后评价的基 本问题之一，它是使用者评判建成环境好 坏、优劣的重要测度标准。为弥补目前环境 评价尺度研究方面的缺失，建立与儿童使用 主体相一致的建成环境评价尺度，对儿童常 用语义量词进行汇总和筛选，采用五级线 分刻度方法进行问卷调查研究。基于儿童的 理解，通过问卷试验分析，结果表明：双侧 5级区间评价尺度为：很（负面）；有点（负 面）；中等；有点（正面）；很（正面）；单侧 5级区间评价尺度为：不；好像有点；比较； 很；特别。     

Prediction of cooling efficiency of forced-air precooling systems based on optimized differential evolution and improved BP neural network

This paper proposes an approach to predict the efficiency of forced-air cooling of fresh apples that combines the optimized differential evolution (DE) algorithm and the back-propagation (BP) neural network algorithm. First, to balance population diversity and fast convergence, the individual mutation operation of the basic DE algorithm was optimized by dividing the entire population into two equal parts according to the fitness value of individuals, and DE-best-1 and DE-current-to-rand-1 are used as individual mutation operations for the superior- and inferior-part individuals, respectively. Moreover, the selection operation of basic DE was also changed by using a crowding scheme, which helps maintain population diversity and discover more regions containing the global optima. Second, an optimized DE-BP neural network model was established by using the optimized DE to determine the initial weights and thresholds of the BP neural network to avoid being trapped in local minima, following which the effect of input parameters on the network output was subjected to a comprehensive sensitivity analysis based on the trained neural network. The results show that the optimized DE-BP model accurately predicts the efficiency with which apples are cooled. Furthermore, the airflow velocity and total opening area have a significant negative correlation with the average apple temperature and a positive correlation with the cooling rate of the apples. Finally, the most important factor influencing the cooling efficiency of the pre-cooling system is the total opening area of the ventilated packaging.     

基于多尺度高斯核的分布式正则化回归学习算法

针对工业、信息等领域出现的基于较大规模、非平稳变化复杂数据的回归问题,已有算法在计算成本及拟合效果方面无法同时满足要求.因此,文中提出基于多尺度高斯核的分布式正则化回归学习算法.算法中的假设空间为多个具有不同尺度的高斯核生成的再生核Hilbert空间的和空间.考虑到整个数据集划分的不同互斥子集波动程度不同,建立不同组合系数核函数逼近模型.利用最小二乘正则化方法同时独立求解各逼近模型.最后,通过对所得的各个局部估计子加权合成得到整体逼近模型.在2个模拟数据集和4个真实数据集上的实验表明,文中算法既能保证较优的拟合性能,又能降低运行时间.