Word length and lexical activation: Longer is better.

Many models of spoken word recognition posit the existence of lexical and sublexical representations, with excitatory and inhibitory mechanisms used to affect the activation levels of such representations. Bottom-up evidence provides excitatory input, and inhibition from phonetically similar representations leads to lexical competition. In such a system, long words should produce stronger lexical activation than short words, for 2 reasons: Long words provide more bottom-up evidence than short words, and short words are subject to greater inhibition due to the existence of more similar words. Four experiments provide evidence for this view. In addition, reaction-time-based partitioning of the data shows that long words generate greater activation that is available both earlier and for a longer time than is the case for short words. As a result, lexical influences on phoneme identification are extremely robust for long words but are quite fragile and condition-dependent for short words. Models of word recognition must consider words of all lengths to capture the true dynamics of lexical activation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

移动通信系统中功率控制研究

在阐述功率控制在移动通信系统中的发展过程的基础上，着重研究了WCDMA系统的功率控制，最后对功率控制未来的研究方向做了简要的分析。     

Electrical conductivity of ferroelectric sodium vanadate,rubidium vanadate,cesium vanadate and their solid solutions

The d.c. electrical conductivity of sodium vanadate, rubidium vanadate, cesium vanadate and their solid solutions sodium-rubidium vanadate and sodium-cesium vanadate were studied by a two-probe method in the temperature range covering their transition points. The electrical conductivity shows sharp change at the phase transition temperature of these materials. In NaVO₃, RbVO₃ and CsVO₃, increase in d.c. conductivity is observed in the ferroelectric region while nonlinearities are observed above transition temperatures. In solid solutions, the activation energy in the paraelectric state is higher than that in the ferroelectric state and depends upon sodium concentration.     

Selectivity Enhancement to the Exclusive Formation of Ethyltoluenes and Hydrogen During Dehydroalkylation of Toluene with Ethane

The dehydroalkylation of toluene with ethane to the isomeric ethyltoluenes was studied on 0.4Pt/H-ZSM-5 at varying contact times (1/WHSV). At a high contact time of 1.0 h, toluene disproportionation and hydrogenolysis reactions dominate, resulting in low selectivity to the desired ethyltoluenes via the alkylation reaction. However, at a low contact time of 0.12 h side reactions are eliminated, resulting in maximum selectivities to the kinetically favored ethyltoluenes and hydrogen. Results at high selectivities to ethyltoluenes provide significant insight into reaction pathways.     

Carbon nanofibers as hydrogen adsorbing materials for power sources

Porous carbon nanofibers are synthesized by CVD method from acetylene with use of iron-containing catalysts. Activation of the nanofibers in melted potassium hydroxide results in increasing surface area from initial 300–400 m² g⁻¹ to 1700 m² g⁻¹. As follows from XRD data, activated nanofibers do not contain regular packages of graphene layers, but retain high electric conductivity. Deposition of copper improves electrochemical hydrogen storing characteristics of carbon nanofibers. Carbon nanomaterials obtained can be used as hydrogen storing materials in batteries instead of hydride forming metals.     

Ultrasound‐activated Knoevenagel condensation of malononitrile with carbonylic compounds catalysed by alkaline‐doped saponites

α,β‐Unsaturated nitriles have been synthesized by Knoevenagel condensation of a carbonylic compound with malononitrile, assisted by sonochemical irradiation. Two alkaline‐promoted clays (Li⁺‐ and Cs⁺‐exchanged saponites) have been employed as catalysts. The influence of the carbonylic compound (benzaldehyde or cyclohexanone) and the use of a solvent on the catalytic activity have been studied. Remarkable increase in the conversion values has been found when the reaction is activated by ultrasound, as compared with the thermal activation. In this green, solvent‐free procedure, α,β‐unsaturated nitriles have been produced in very high yields (97%) when the Cs⁺‐saponite is used as catalyst. Copyright © 2004 Society of Chemical Industry     

巯基棉预浓集—中子活化法测定水泥及其浸出水中的微量汞

在不同酸度下巯基棉可以从溶液中富集和分离Au、As、Ag、Br、Cu、Ca Co、InHg、Ni、Se、Sb、Sn、Pb、W、Fe和In等30多种元素。由于用巯基棉吸附待测元素后不必洗脱,因此大大提高了富集能力,可用于海水、地下水、地表水及工业废水中一些元素的测量。本文用巯基棉富集后进行中子活化分析测定水泥及其浸出水中的汞。     

硫脲型整合树脂在分析上的应用 Ⅰ.岩样中微量银的中子活化分析

前言银和其他贵金属元素一样,在地壳中比较稀少,按其自然丰度为第67号元素,平均含量仅0.07 ppm。由于地质样品成分非常复杂,为测定其微量银,必须进行严格的化学分离。但是迄今文献中报道的许多分离分法,步骤都相当冗长,一般采用氯化银反     

Thermally induced microstructural changes in cotton fibers: A free‐volume study

I measured positron lifetime in natural polymer–cotton fibers as a function of isochronal annealing temperature in the range 27–290°C. The variations in the positron results indicated structural changes occurring in the cotton fibers and determined the glass‐transition temperature as 80°C. Activation energies were measured separately for the crystalline and amorphous regions, indicating the versatility of the technique. These values were close to the O? H bond dissociation energy, suggesting O? H bond dissociation, the most probable process occurring under thermal treatment. As an extension of the positron results, the molecular weight of the cotton fibers was determined to be 1,200,000 based on free volume, which was within the range suggested for cotton. There seemed to be an indication that crosslinking changed the spiral structure of cotton fibers to the network type. However, this needs to be validated by other measurements. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 3336–3345, 2002     

Learning and Revising User Profiles: The Identification of Interesting Web Sites

We discuss algorithms for learning and revising user profiles that can determine which World Wide Web sites on a given topic would be interesting to a user. We describe the use of a naive Bayesian classifier for this task, and demonstrate that it can incrementally learn profiles from user feedback on the interestingness of Web sites. Furthermore, the Bayesian classifier may easily be extended to revise user provided profiles. In an experimental evaluation we compare the Bayesian classifier to computationally more intensive alternatives, and show that it performs at least as well as these approaches throughout a range of different domains. In addition, we empirically analyze the effects of providing the classifier with background knowledge in form of user defined profiles and examine the use of lexical knowledge for feature selection. We find that both approaches can substantially increase the prediction accuracy.