Nanocrystalline TiO2 photosensitized with natural polymers with enhanced efficiency from 400 to 600 nm

TiO₂ sensitization for solar applications requires not only efficient but also stable and inexpensive sensitizers. Different condensed tannins extracted from bark wastes of tropical wood trees were studied as possible sensitizers of TiO₂. These natural polymers adhere strongly to the TiO₂ even from aqueous solutions. Absorption spectra are presented for 1 mM aqueous sensitizing solutions prepared with lyophilized condensed tannins which absorb light in the visible range. Spectral photocurrent measurements and I–V characterization show that no bias is required for electron injection to the TiO₂ from all studied condensed tannins. Incident photon to current efficiency (IPCE) analysis indicates that surface complexation originates absorption bands with different electron injection efficiencies. These play a dominant role in determining IPCE spectral shape. We propose that surface modification by the sensitizer changes the surface trap density, thereby decreasing recombination losses.     

用VB解决CAI中的几个问题

本文利用Windows的API函数将VB窗体前置,避免教师在CAI过程中频繁切换活动窗口,并通过VB控件将各种不同的电子文档内容在窗体中显示出来。     

MIP-CGP工艺专用催化剂CGP-1的开发与应用

阐述了生产汽油组分满足欧Ⅲ排放标准并多产丙烯的催化裂化工艺（简称MIP-CGP）专用催化剂（简称CGP-1）的研究开发与工业应用结果。CGP-1催化剂的基质具有良好的容炭性能，使活性组元受到良好保护，其优势作用在第二反应区得以充分发挥，具有更高的氢转移活性和强的汽油小分子烯烃裂化活性。中国石化九江分公司和镇海炼化公司的MIP-CGP工业试验标定结果表明，与常规FCC相比，采用CGP-1催化剂的MIP-CGP技术在生产烯烃体积分数小于18％的汽油组分的同时，丙烯产率达到8％以上。此外，汽油诱导期大幅提高，抗爆指数增加；总液体收率有所提高，干气产率下降，焦炭选择性良好。     

Effect of sampling density on the measurement of stream condition indicators in two lowland Australian streams

There is widespread application of indicators to the assessment of environmental condition of streams. These indicators are intended for use by managers in making various comparative and absolute assessments and often have a role in resource allocation and performance assessment. Therefore, the problem of formally defining confidence in the results is important but difficult because the sampling strategies used are commonly based on a compromise between the requirements of statistical rigour and the pragmatic issues of access and resources. It is rare to see this compromise explicitly considered and consequently there is seldom quantification of the uncertainty that could affect the confidence a manager has in an indicator. In this paper, we present a method for quantitatively assessing the tradeoffs between sampling density and uncertainty in meeting various monitoring objectives. Assessments using judgement‐based representative reaches are shown to be unreliable; instead a sampling approach is recommended based on the random selection of measuring sites. A detailed dataset was collected along two streams in Victoria, Australia, and the effect of sampling density was assessed by subsampling from this dataset with precision related to the number of sites assessed per reach length and the intensity of the sampling at each site. The sampling scheme to achieve a given precision is shown to depend on the monitoring objective. In particular, three objectives were considered: (1) making a baseline assessment of current condition; (2) change detection; and (3) detection of a critical threshold in condition. Change detection is shown to be more demanding than assessing baseline condition with additional sampling effort required to achieve the same precision. Sampling to detect a critical threshold depends on nominating acceptable values of Type I and II error and the size of the effect to be detected. Copyright © 2006 John Wiley & Sons, Ltd.     

Novel tiO2 nanocatalysts for wastewater purification: tapping energy from the sun.

Water treatment using TiO2 semiconductor as a durable heterogeneous photocatalyst has been the focus of environmentalists in recent years. Currently, we developed an inexpensive and highly efficient approach for synthesizing nitrogen-doped TiO2 with lower band-gap energy that can respond to visible light. Doping on the molecular scale led to an enhanced nitrogen concentration of up to 21.8%. Reflectance measurements showed the synthesized N-doped TiO2 nanoparticles are catalytically active with the absorbance that extends into the visible region up to 600 nm. The water purification potential of this new class of compound was evaluated by studying the photodegradation of Acid Orange 7 (AO7) and E. coli. Experiments were conducted to compare the photocatalytic activities of N-doped TiO2 nanocatalysts and commercially available Degussa P25 power under identical solar light exposure. N-doped TiO2 demonstrated superior photocatalytic activities in both chemical compound degradation and bactericidal reactions. The result of this study shows the potential of applying new generations of catalyst for wastewater purification and disinfection.     

Entropy of multidimensional cellular automata

Since the topological entropy of a vast class of two-dimensional cellular automata (CA) is infinite, of interest is the possibility to renormalize it so that to obtain a positive finite value. We find the asymptotics of the information function of a multidimensional CA and, accordingly, introduce the renormalized topological entropy as a coefficient of this asymptotics. We describe some properties of the introduced quantity, in particular, its positivity for CA of the type of “The Game of Life.” Also, we give an example of an explicit evaluation of this parameter for a particular cellular automaton.     

Radioecological state of the territory and water area in Guba Andreev

The radioecological conditions which developed on the territory over the long operating time of the object of the naval fleet in Guba Andreev are described. The results of an analysis of the sources of the real and potential danger and measures to prevent dangerous effects for the environment and the workers at the time remediation work is performed are discussed. __________ Translated from Atomnaya énergiya, Vol. 101, No. 1, pp. 49–55, July, 2006.     

Learning with belief levels

We study learning of predicate logics formulas from “elementary facts,” i.e. from the values of the predicates in the given model. Several models of learning are considered, but most of our attention is paid to learning with belief levels. We propose an axiom system which describes what we consider to be a human scientist's natural behavior when trying to explore these elementary facts. It is proved that no such system can be complete. However we believe that our axiom system is “practically” complete. Theorems presented in the paper in some sense confirm our hypothesis.     

Results of a User Study on 2D Hurricane Visualization

We present the results from a user study looking at the ability of observers to mentally integrate wind direction and magnitude over a vector field. The data set chosen for the study is an MM5 (PSU/NCAR Mesoscale Model) simulation of Hurricane Lili over the Gulf of Mexico as it approaches the southeastern United States. Nine observers participated in the study. This study investigates the effect of layering on the observer's ability to determine the magnitude and direction of a vector field. We found a tendency for observers to underestimate the magnitude of the vectors and a counter‐clockwise bias when determining the average direction of a vector field. We completed an additional study with two observers to try to uncover the source of the counter‐clockwise bias. These results have direct implications to atmospheric scientists, but may also be able to be applied to other fields that use 2D vector fields.     

Assessing continuous bivariate effects among different groups through nonparametric regression models: An application to breast cancer detection

In many applications, the joint effect of two continuous covariates on the target binary response may vary across groups defined by levels of a given factor. A testing procedure that would enable this type of surface-by-factor interactions to be detected has been designed. To accomplish this goal, a logistic generalized additive model (GAM) with bivariate continuous interactions varying across groups defined by levels of a factor is considered. A local scoring algorithm based on local linear kernel smoothers was implemented to estimate the proposed logistic GAM. Bootstrap resampling techniques were used for the purpose of testing for factor-by-surface interactions. Given the high computational cost involved, binning techniques were used to speed up computation in the estimation and testing processes. The adequacy of the bootstrap-based test was assessed by means of a simulation study. If a factor-by-surface interaction is detected in the model, it is then established that the use of the odds-ratio curves is very useful in obtaining a direct interpretation of the fitted model. The benefits of using this methodology when analyzing real data are illustrated by applying the technique to the outputs produced by a computerized system dedicated to the early detection of breast cancer.