Electrocatalytic Reduction of CO2 to Ethylene by Molecular Cu‐Complex Immobilized on Graphitized Mesoporous Carbon

The electrochemical reduction of carbon dioxide (CO₂) to hydrocarbons is a challenging task because of the issues in controlling the efficiency and selectivity of the products. Among the various transition metals, copper has attracted attention as it yields more reduced and C2 products even while using mononuclear copper center as catalysts. In addition, it is found that reversible formation of copper nanoparticle acts as the real catalytically active site for the conversion of CO₂ to reduced products. Here, it is demonstrated that the dinuclear molecular copper complex immobilized over graphitized mesoporous carbon can act as catalysts for the conversion of CO₂ to hydrocarbons (methane and ethylene) up to 60%. Interestingly, high selectivity toward C2 product (40% faradaic efficiency) is achieved by a molecular complex based hybrid material from CO₂ in 0.1 m KCl. In addition, the role of local pH, porous structure, and carbon support in limiting the mass transport to achieve the highly reduced products is demonstrated. Although the spectroscopic analysis of the catalysts exhibits molecular nature of the complex after 2 h bulk electrolysis, morphological study reveals that the newly generated copper cluster is the real active site during the catalytic reactions.     

D-limonene Inhibits Pentylenetetrazole-Induced Seizure via Adenosine A2A Receptor Modulation on GABAergic Neuronal Activity

Background: Epilepsy is a chronic neurological disorder characterized by the recurrence of seizures. One-third of patients with epilepsy may not respond to antiseizure drugs. Purpose: We aimed to examine whether D-limonene, a cyclic monoterpene, exhibited any antiseizure activity in the pentylenetetrazole (PTZ)-induced kindling mouse model and in vitro. Methods: PTZ kindling mouse model was established by administering PTZ (30 mg/kg) intraperitoneally to mice once every 48 h. We performed immunoblot blots, immunohistochemistry (IHC), and high-performance liquid chromatography (HPLC) analysis after the behavioral study. Results: An acute injection of PTZ (60 mg/kg) induced seizure in mice, while pretreatment with D-limonene inhibited PTZ-induced seizure. Repeated administration of PTZ (30 mg/kg) increased the seizure score gradually in mice, which was reduced in D-limonene (10 mg/kg)-pretreated group. In addition, D-limonene treatment increased glutamate decarboxylase-67 (GAD-67) expression in the hippocampus. Axonal sprouting of hippocampal neurons after kindling was inhibited by D-limonene pretreatment. Moreover, D-limonene reduced the expression levels of Neuronal PAS Domain Protein 4 (Npas4)-induced by PTZ. Furthermore, the adenosine A2A antagonist {"type":"entrez-protein","attrs":{"text":"SCH58261","term_id":"1052882304","term_text":"SCH58261"}}SCH58261 and ZM241385 inhibited anticonvulsant activity and gamma-aminobutyric acid (GABA)ergic neurotransmission-induced by D-limonene. Conclusion: These results suggest that D-limonene exhibits anticonvulsant activity through modulation of adenosine A2A receptors on GABAergic neuronal function.     

Collection efficiency of liquid‐based samplers for fungi in indoor air

This study assessed the collection efficiency (CE) of two popularly used sampling devices (BioSampler and Coriolis sampler) for fungal aerosols. Phosphate‐buffered saline (PBS) supplemented with or without surfactant (Tween‐20, Tween‐80, or Triton X‐100) and antifoam agent was prepared and used as collection liquids. The agar impactor (BioStage) was simultaneously operated with liquid‐based samplers to collect fungi from seven sites located at a university building, public library, and animal farming. Fungal concentrations determined by liquid samplers were divided by those by BioStage, and the ratio values represented CE. Results indicate that the CE of BioSampler was superior to that of Coriolis (P = 0.0001) and the PBS containing surfactant collected fungi better than that without surfactant (P < 0.0001), whereas antifoam agent showed no influence (P = 0.8). Moreover, fungal concentrations determined by BioSampler with surfactant‐added PBS were statistically indifferent from those by BioStage (P > 0.05) with a Spearman correlation coefficient of 0.81‐0.83 (P < 0.01). In addition to sampler and collection liquid, sampling location was also identified as a significant CE factor (P = 0.006), implying potential influences by fungal genera in the studied fields. Overall, BioSampler with surfactant‐supplemented PBS (eg, Triton X‐100) is recommended considering the great CE and compatibility with a variety of analytical assays.     

Predicting visual similarity between colour palettes

This work is concerned with the prediction of visual colour difference between pairs of palettes. In this study, the palettes contained five colours arranged in a horizontal row. A total of 95 pairs of palettes were rated for visual difference by 20 participants. The colour difference between the palettes was predicted using two algorithms, each based on one of six colour-difference formulae. The best performance (r² = 0.86 and STRESS = 16.9) was obtained using the minimum colour-difference algorithm (MICDM) using the CIEDE2000 equation with a lightness weighing of 2. There was some evidence that the order (or arrangement) of the colours in the palettes was a factor affecting the visual colour differences although the MICDM algorithm does not take order into account. Application of this algorithm is intended for digital design workflows where colour palettes are generated automatically using machine learning and for comparing palettes obtained from psychophysical studies to explore, for example, the effect of culture, age, or gender on colour associations.     

基于注意力机制与文本信息的用户关系抽取

随着社交媒体的发展,用户之间的关系网络对于社交媒体的分析有很大的帮助。因此,该文主要研究用户好友关系检测。以往的关于用户好友关系抽取的研究主要基于社交媒体上的结构化信息,比如其他好友关系,用户的不同属性等。但是,很多时候用户本身并没有大量的好友信息存在,同时也不一定有很多确定的属性。因此,我们希望基于用户发表的文本信息来对用户关系进行预测。不同于以往的潜在好友推荐算法,该文提出了一种基于注意力机制以及长短时记忆网络(long short-term memory,LSTM)的好友关系预测模型,将好友之间的评论分开处理,通过分析用户之间的评论来判断是否具备一定的好友关系。该模型将好友双方信息拼接后的结果作为输入,并将注意力机制应用于LSTM的输出。实验表明,用户之间的评论对于好友关系预测确实有较大的实际意义,该文提出的模型较之于多个基准系统的效果,取得了明显的提升。在不加入任何其它非文本特征的情况下,实验结果的准确率达到了77%。     

溪洛渡水电站导流洞布置设计

溪洛渡水电站施工期采用左、右岸各布置3条导流洞的施工导流方案,无论是导流洞规模、单洞泄流量还是导流洞断面尺寸均居国内已建和在建导流洞的前列,特别是6条大断面尺寸的导流洞布置规模,在世界上位居首位。本文简要介绍了溪洛渡导流洞布置设计情况。     

An effective coding approach for multiobjective integrated resource selection and operation sequences problem

In this paper, we consider an integrated Resource Selection and Operation Sequences (iRS/OS) problem in Intelligent Manufacturing System (IMS). Several kinds of objectives are taken into account, in which the makespan for orders should be minimized; workloads among machine tools should be balanced; the total transition times between machines in a local plant should also be minimized. To solve this multiobjective iRS/OS model, a new two vectors-based coding approach has been proposed to improve the efficiency by designing a chromosome containing two kinds of information, i.e., operation sequences and machine selection. Using such kind of chromosome, we adapt multistage operation-based Genetic Algorithm (moGA) to find the Pareto optimal solutions. Moreover a special technique called left-shift hillclimber has been used as one kind of local search to improve the efficiency of our algorithm. Finally, the experimental results of several iRS/OS problems indicate that our proposed approach can obtain best solutions. Further more comparing with previous approaches, moGA performs better for finding Pareto solutions. Received: May 2005/Accepted: December 2005     

针对不同地质目标的叠前时间偏移成像解释评价

随着计算机硬件和地震勘探成像技术的发展，叠前时间偏移正逐步替代常规的NMO加DMO加叠后时间偏移成为地震数据成像处理方法的主流。但对于不同的地质目标，叠前时间偏移的成像效果是否优于常规NMO加DMO加叠后时间偏移的成像效果呢？为此，从地震数据成像处理方法、处理流程和处理参数等方面进行了讨论，并基于某地区三维数据常规处理结果和叠前时间偏移处理结果，针对不同地质目标进行了剖析与评价。认为：叠前时间偏移成像的垂向分辨率较常规处理明显降低，但对于空间波阻抗变化明显的河流和断层，叠前时间偏移成像的空间分辨率要高于常规处理；对于小于1／4波长的叠置薄储层，叠前时间偏移成像的垂向和空间分辨率低于常规处理结果。     

Knowledge-based control and case-based diagnosis based upon empirical knowledge and fuzzy logic for the SBR plant.

Because biological wastewater treatment plants (WWTPs) involve a long time-delay and various disturbances, in general, skilled operators manually control the plant based on empirical knowledge. And operators usually diagnose the plant using similar cases experienced in the past. For the effective management of the plant, system automation has to be accomplished based upon operating recipes. This paper introduces automatic control and diagnosis based upon the operator's knowledge. Fuzzy logic was employed to design this knowledge-based controller because fuzzy logic can convert the linguistic information to rules. The controller can manage the influent and external carbon in considering the loading rate. The input of the controller is not the loading rate but the dissolved oxygen (DO) lag-time, which has a strong relation to the loading rate. This approach can replace an expensive sensor, which measures the loading rate and ammonia concentration in the reactor, with a cheaper DO sensor. The proposed controller can assure optimal operation and prevent the over-feeding problem. Case-based diagnosis was achieved by the analysis of profile patterns collected from the past. A new test profile was diagnosed by comparing it with template patterns containing normal and abnormal cases. The proposed control and diagnostic system will guarantee the effective and stable operation of WWTPs.     

连续波半主动雷达制导空空导弹截获跟踪距离计算

分析了连续波半主动雷达制导导弹导引头工作电磁环境和对武器系统攻击区的影响，建立了热噪声和杂波干扰环境下导引头截获距离方程，分析推导了直波泄漏干扰，地杂波干扰的计算公式，并在此基础上给出了导弹允许攻击区计算公式。