Design of Deep Convolution Neural Networks for categorical signature classification of raw panchromatic satellite images

Multimedia Tools and Applications - Remote Sensing categorical signature classification has gained significant implications on spatial resolution image analysis due to differences in the...     

Influence of Titanium Excess in a Ti–Si Reaction Mixture on the Synthesis of a Composite in a Combustion Wave

Theoretical Foundations of Chemical Engineering - On the basis of the classic concepts of the theory of solid-phase combustion, for the first time, a model with a detailed scheme of chemical...     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Effect of Drosophila suzukii on Blueberry VOCs: Chemical Cues for a Pupal Parasitoid,Trichopria anastrephae

Journal of Chemical Ecology - Biocontrol agents such as parasitic wasps use long-range volatiles and host-associated cues from lower trophic levels to find their hosts. However, this chemical...     

Synthesis of Hollow Three-Dimensional Channels LiNi_(0.5)Mn_(1.5)O_4 Microsphere by PEO Soft Template Assisted with Solvothermal Method

A appropriate size with three-dimension(3 D) channels for lithium diffusion plays an important role in constructing highperforming LiNi_(0.5)Mn_(1.5)O_4(LNMO) cathode materials, as it can not only reduce the transport path of lithium ions and electrons, but also reduce the side effects and withstand the structural strain in the process of repetitive Li~+ intercalation/deintercalation. In this work, an e fficient method for designing the hollow LNMO microsphere with 3 D channels structure by using polyethylene oxide(PEO) as soft template agent assisted solvothermal method is proposed. Experimental results indicate that PEO can make the reagents mingle evenly and nucleate slowly in the solvothermal process, thus obtaining a homogeneous distribution of carbonate precursors. In the final LNMO products, the hollow 3 D channels structure obtained by the decomposition of PEO and carbonate precursor in the calcination can provide abundant electroactive zones and electron/ion transport paths during the charge/discharge process, which benefits to improve the cycling performance and rate capability. The LNMO prepared by adding 1 g PEO possesses the most outstanding electrochemical performance, which presented an excellent discharge capacity of 143.1 mAh g~(-1) at 0.1 C and with a capacity retention of 92.2% after 100 cycles at 1 C. The superior performance attributed to the 3 D channels structure of hollow microspheres, which provide uninterrupted conductive systems and therefore achieve the stable transfer for electron/ion.     

盾构隧道施工物料无人运输发展现状及关键技术

盾构隧道施工物料无人运输有助于提升运输效率、降低运输成本、减少运输安全事故率。与公路汽车无人驾驶、港口车辆无人驾驶、轨道交通无人驾驶等逐步成熟的无人驾驶技术不同，在隧道场景下实施施工物料无人运输存在运输物料种类繁多、运输调度困难、地下定位信号拒止、狭窄车道频繁会车、行车路面工况复杂、地上地下联动响应慢等诸多挑战。从实现盾构隧道施工物料无人运输的关键问题分析入手，综述当前盾构隧道施工物料运输方式、运输需求、无人运输发展现状及存在的挑战，提出盾构隧道施工物料无人运输的五大关键技术：多种类物料智能货控能效管理技术，无人化垂直装卸门机控制技术，多传感器融合同步定位与地图构建技术，隧道复杂环境路径规划与自主避障技术，隧-地一体化联动响应的高可靠性无线通信技术。     

Influence of Continuous Wave Interference on the Efficiency of the Non-Threshold Search Procedure for a Noise-Like Signal by Delay Time with Transition to the Frequency Domain

Journal of Communications Technology and Electronics - A statistical study of the effectiveness of the non-threshold search procedure for a noise-like phase-shift keyed signal by the delay time is...     

A novel strategy based on salp swarm algorithm for extracting the maximum power of proton exchange membrane fuel cell

Cell temperature and water content of the membrane have a significant effect on the performance of fuel cells. The current-power curve of the fuel cell has a maximum power point (MPP) that is needed to be tracked. This study presents a novel strategy based on a salp swarm algorithm (SSA) for extracting the maximum power of proton-exchange membrane fuel cell (PEMFC). At first, a new formula is derived to estimate the optimal voltage of PEMFC corresponding to MPP. Then the error between the estimated voltage at MPP and the actual terminal voltage of the fuel cell is fed to a proportional-integral-derivative controller (PID). The output of the PID controller tunes the duty cycle of a boost converter to maximize the harvested power from the PEMFC. SSA determines the optimal gains of PID. Sensitivity analysis is performed with the operating fuel cell at different cell temperature and water content of the membrane. The obtained results through the proposed strategy are compared with other programmed approaches of incremental resistance method, Fuzzy-Logic, grey antlion optimizer, wolf optimizer, and mine-blast algorithm. The obtained results demonstrated high reliability and efficiency of the proposed strategy in extracting the maximum power of the PEMFC.     

BS960E高强钢激光-电弧复合焊接头氢脆行为研究

氢脆具有很强的微观组织敏感性,威胁着各类高强结构材料的安全服役.采用激光-电弧复合焊工艺对BS960E型高强钢进行焊接,并对接头在原位电化学充氢的条件下进行慢应变速率(10-5s-1)拉伸试验,结合微观组织和断裂特征进行分析并对接头的氢脆行为进行研究.结果 表明,焊接热循环所形成的富马氏体中的细晶区可以使接头表现出一定的氢脆敏感性,马氏体较大的氢扩散系数和较低的氢溶解度以及氢在晶界上的快速扩散是引起接头对氢脆敏感的主要原因,通过控制焊接工艺参数可抑制焊接热循环所引起的马氏体转变量,能够降低BS960E型高强钢激光-电弧复合焊接头的氢脆敏感性.     

Thermal prehistory,structure and high-temperature thermodynamic properties of Y2O3-CeO2 and Y2O3-ZrO2-CeO2 solid solutions

Ceria-based solid solutions are important materials for high- and medium-temperature electrochemical applications. However, the stabilities of both binary and ternary ceria-based solid solutions are insufficient at elevated temperatures, which limits their application as solid electrolytes or SOFC cathodes. Data on the high-temperature stability of ceria-based ceramics are unavailable in the literature. In the present study, we report a thermodynamic stability investigation of Y₂O₃-CeO₂ and Y₂O₃-ZrO₂-CeO₂ solid solutions. The thermal prehistories of binary and ternary systems were investigated using STA, XRD, and ESCA techniques. The vaporization processes were investigated in the temperature range of 1577–2227°С via the Knudsen effusion mass spectrometry technique. Using data on the component activity in solid-phase thermodynamic properties of Y₂O₃-CeO₂ solid solutions, which is represented as the Gibbs energy, the excess Gibbs energy was calculated as a function of the ceria mol. %. It was shown that the reduction of Ce⁴⁺ to Ce³⁺ in Y₂O₃-CeO₂ and Y₂O₃-ZrO₂-CeO₂ solid solutions corresponds to less-negative Gibbs energy compared to ZrO₂-CeO₂ solid solutions.