Synthesis of magnetically recoverable ferrite (MFe2O4, M Co,Ni and Fe)-supported TiO2 photocatalysts for decolorization of methylene blue

Effects of ferrite materials as supports (CoFe₂O₄, NiFe₂O₄, and Fe₃O₄) on nano-TiO₂ were elucidated by their use in the oxidation of methylene blue. These photocatalysts, which were synthesized by co-precipitation, were characterized by XRD, SEM, EDS and VSM. The crystalline phase of TiO₂ onto magnetic MFe₂O₄ was formed by anatase and rutile. TiO₂/CoFe₂O₄ exhibited the strongest magnetic property of the prepared catalysts, and the photocatalytic efficiencies followed the order TiO₂/CoFe₂O₄ > TiO₂/NiFe₂O₄ > TiO₂/Fe₃O₄. MB decolorization was enhanced with the amount of TiO₂ on the photocatalyst, and was moderately affected by the extent of structural distortion of ferrite supports.     

Lead-free sodium niobate nanowires with strong piezo-catalysis for dye wastewater degradation

In this work, the hydrothermally-synthesized sodium niobate nanowires were used to decompose Rhodamine B dye solution through the piezo-catalytic effect. With the sodium niobate catalyst, a high piezo-catalytic degradation ratio of ～80% was achieved under the excitation of vibration for the Rhodamine B dye solution (～5?mg/l). These active species in the catalytic process, hydroxyl radicals and superoxide radicals with the strong oxidation ability, were also observed, which confirmed the key role of piezoelectric effect for piezo-catalysis. The piezo-catalysis of sodium niobate nanowires provides a high-efficiency and reusable tool in application in depredating the dye wastewater.     

Mining citizen emotions to estimate the urgency of urban issues

Crowdsourcing technology offers exciting possibilities for local governments. Specifically, citizens are increasingly taking part in reporting and discussing issues related to their neighborhood and problems they encounter on a daily basis, such as overflowing trash-bins, broken footpaths and lifts, illegal graffiti, and potholes. Pervasive citizen participation enables local governments to respond more efficiently to these urban issues. This interaction between citizens and municipalities is largely promoted by civic engagement platforms, such as See-Click-Fix, FixMyStreet, CitySourced, and OpenIDEO, which allow citizens to report urban issues by entering free text describing what needs to be done, fixed or changed. In order to develop appropriate action plans and priorities, government officials need to figure out how urgent are the reported issues. In this paper we propose to estimate the urgency of urban issues by mining different emotions that are implicit in the text describing the issue. More specifically, a reported issue is first categorized according to the emotions expressed in it, and then the corresponding emotion scores are combined in order to produce a final urgency level for the reported issue. Our experiments use the SeeClickFix hackathon data and diverse emotion classification algorithms. They indicate that (i) emotions can be categorized efficiently with supervised learning algorithms, and (ii) the use of citizen emotions leads to accurate urgency estimates. Further, using additional features such as the type of issue or its author leads to no further accuracy gains.     

PCC载体氧化剂的制备及应用研究

制备得到各种有代表性的氯铬酸吡啶(PCC)无机载体氧化试剂,以苯甲醇选择性氧化成苯甲醛为探针反应,考察了载体、反应条件对氧化反应效率的影响,控制各载体氧化剂中PCC的负载量均为1.8 mmol/g。室温下反应,搅拌时间为30 m in,苯甲醇的氧化反应产率为:分子筛65.8%,活性炭75.4%,氧化铝94.6%,硅胶96.9%,相同条件下PCC的产率为65.8%。硅胶是制备负载PCC的优良载体,在载体氧化剂对苯甲醇的氧化反应中,一定范围内增加反应时间和载体加入量都可以提高氧化产率。     

Supercapacitors based on conducting polymers/nanotubes composites

Three types of electrically conducting polymers (ECPs), i.e. polyaniline (PANI), polypyrrole (PPy) and poly-(3,4-ethylenedioxythiophene) (PEDOT) have been tested as supercapacitor electrode materials in the form of composites with multiwalled carbon nanotubes (CNTs). The energy storage in such a type of composite combines an electrostatic attraction as well as quick faradaic processes called pseudo-capacitance. It has been shown that carbon nanotubes play the role of a perfect backbone for a homogenous distribution of ECP in the composite. It is well known that pure conducting polymers are mechanically weak, hence, the carbon nanotubes preserve the ECP active material from mechanical changes (shrinkage and breaking) during long cycling. Apart of excellent conducting and mechanical properties, the presence of nanotubes improves also the charge transfer that enables a high charge/discharge rate. For an optimal use of ECPs in electrochemical capacitors, a special electrode composition with ca. 20 wt.% of CNTs and a careful selection of the potential range is necessary. The capacitance values ranging from 100 to 330 F g⁻¹ could be reached for different asymmetric configurations with a capacitor voltage from 0.6 to 1.8 V. It is also noteworthy that such a type of ECP/CNTs composite does not need any binding substance that is an important practical advantage.     

Project-based mechanisms for emissions reductions: balancing trade-offs with baselines

Project-based mechanisms for emissions reductions credits, like the Clean Development Mechanism, pose important challenges for policy design because of several inherent characteristics. Participation is voluntary, so it will not occur without sufficient credits. Evaluating reductions requires assigning an emissions baseline for a counterfactual that cannot be measured. Some investments have both economic and environmental benefits and might occur anyway. Uncertainty surrounds both emissions and investment returns, and parties to the project are likely to have more information than the certifying authority. The certifying agent is limited in its ability to design a contract that would reveal investment intentions. As a result, rules for benchmarking emissions may be systematically biased to overallocate, and they also risk creating inefficient investment incentives. This paper evaluates, in a situation with asymmetric information, the efficacy of the main baseline rules currently under consideration: historical emissions, an average industry emissions standard, and expected emissions.     

信息技术课堂中情境教学法的应用

情境教学法是教学中常的一种教学方法,本文根据信息技术的学科特点,结合教师创设的情景,阐述了信息技术课堂教学中情境的创设,以及在信息技术教学中的应用应该注意的几个问题。     

Financial distress prediction using support vector machines: Ensemble vs. individual

Financial distress prediction (FDP) is of great importance to both inner and outside parts of companies. Though lots of literatures have given comprehensive analysis on single classifier FDP method, ensemble method for FDP just emerged in recent years and needs to be further studied. Support vector machine (SVM) shows promising performance in FDP when compared with other single classifier methods. The contribution of this paper is to propose a new FDP method based on SVM ensemble, whose candidate single classifiers are trained by SVM algorithms with different kernel functions on different feature subsets of one initial dataset. SVM kernels such as linear, polynomial, RBF and sigmoid, and the filter feature selection/extraction methods of stepwise multi discriminant analysis (MDA), stepwise logistic regression (logit), and principal component analysis (PCA) are applied. The algorithm for selecting SVM ensemble's base classifiers from candidate ones is designed by considering both individual performance and diversity analysis. Weighted majority voting based on base classifiers’ cross validation accuracy on training dataset is used as the combination mechanism. Experimental results indicate that SVM ensemble is significantly superior to individual SVM classifier when the number of base classifiers in SVM ensemble is properly set. Besides, it also shows that RBF SVM based on features selected by stepwise MDA is a good choice for FDP when individual SVM classifier is applied.     

Supply chain trust diagnosis (SCTD) using inductive case-based reasoning ensemble (ICBRE): The case of general competence trust diagnosis

General competence trust among supply chain partners, referring to the trust that a partner holds the general ability of fulfilling contracts, is a critical factor to ensure effective cooperation in a supply chain, especially in the current financial crisis. The method of supply chain trust diagnosis (SCTD) is to evaluate whether or not a partner holds such competence. This research devotes to an early investigation on diagnosing competence trust of supply chain with the method of inductive case-based reasoning ensemble (ICBRE). The so-called supply chain trust diagnosis with inductive case-based reasoning ensemble consists of five levels, that is, information level, the level of ratios of general competence states, the level of inductive case-based reasoning, ensemble level, and diagnosis result level. Knowledge for diagnosing competence trust, which composes of a case base, is hidden in data represented by ratios of general competence states. Inductive approach is combined with randomness to construct diverse and good member methods of inductive case-based reasoning. Finally, simple voting is used to integrate outputs of member inductive case-based reasoning methods in order to produce the final diagnosis on whether or not a partner holds the general ability of fulfilling contracts. We statistically validated results of the method of supply chain trust diagnosis with inductive case-based reasoning ensemble by comparing them with those of multivariate discriminant analysis, logistic regression, single Euclidean case-based reasoning, and single inductive case-based reasoning. The results indicate that the method of supply chain trust diagnosis with inductive case-based reasoning ensemble significantly improves predictive capability of case-based reasoning in this problem and outperforms all the comparative models by group decision of several decision-making agents and non-strict assumptions like statistical methods.     

访问控制策略描述语言与策略冲突研究

访问控制技术是网络安全防范和保护的主要方法,能保证信息的完整性和机密性。随着计算机、互联网和无线通信技术的高速发展,网络安全问题日益严重,访问控制策略的研究已成为计算机学科的一个热点课题。本文首先介绍了五种主要的访问控制策略描述语言,分析了各自的特点及适用环境;然后总结了访问控制策略冲突产生的原因、类型、冲突检测以及冲突消解方法;最后给出了访问控制策略研究的发展趋势。