非晶态NiB配位催化2-亚丁基环己酮的选择加氢动力学研究

以超细非晶态NiB为催化剂、乙醇为溶剂 ,研究了常压条件下 2 -亚丁基环己酮的选择催化氢化反应。确定了反应对 2 -亚丁基环己酮的反应级数n =1,80℃下准一级反应的速率常数为k =3.4× 10 -3 min-1。同时考察了氢化过程中外扩散的影响以及温度、催化剂用量对反应的影响。求得反应的活化能Ea =16 .391kJ/mol。     

Effects of mixing conditions on the reaction of 3‐octanoylthio‐1‐propyltriethoxysilane during mixing with silica filler and natural rubber

The effects of mixing temperature and mixing time on the reaction of 3‐octanoylthio‐1‐propyltriethoxysilane (NXT silane) during mixing with precipitated silica and natural rubber (NR) were investigated. Results showed that the reaction between NXT silane and precipitated silica can proceed at temperatures above 130°C. Because of the blocking group of NXT silane, the silane–NR coupling reactivity is low, so that the reaction of NXT silane with NR occurs only during the curing period. There is no reaction between NXT silane and NR during mixing, which showed that the mixing time of silica‐filled NR compound containing NXT silane must be longer than 10 min at 150°C to obtain the desired silane coupling efficiency. With increasing mill temperature, the coupling efficiency increases. A high mixing temperature promotes improvement of silane–silica coupling efficiency, although the tensile strength, 100% modulus, 300% modulus, and hardness of NR vulcanizates decrease. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 94: 2295–2301, 2004     

Automatic annotation of tennis games: An integration of audio,vision, and learning

Fully automatic annotation of tennis game using broadcast video is a task with a great potential but with enormous challenges. In this paper we describe our approach to this task, which integrates computer vision, machine listening, and machine learning. At the low level processing, we improve upon our previously proposed state-of-the-art tennis ball tracking algorithm and employ audio signal processing techniques to detect key events and construct features for classifying the events. At high level analysis, we model event classification as a sequence labelling problem, and investigate four machine learning techniques using simulated event sequences. Finally, we evaluate our proposed approach on three real world tennis games, and discuss the interplay between audio, vision and learning. To the best of our knowledge, our system is the only one that can annotate tennis game at such a detailed level.     

多孔陶瓷的制备和性能研究

选用普通陶瓷原料粉为主要原料，适当添加造孔剂(有机细粉碳黑)和高温活性剂，制备出一种性能优良的多孔陶瓷。通过扫描电镜及性能测试分析，探讨了多孔陶瓷的微观结构及性能的影响因数。     

End-capped polystyrene with 8-hydroxyquinoline group by ATRP method

8-Hydroxyqunioline end-capped polystyrene was prepared through atom transfer free radical polymerization (ATRP) with 8-(5-chloromethyl) quinolyl acetate as initiator. The results indicated that this polymerization is a first order reaction with respect to monomer conversion. The molecular weight increased linearly with monomer consumption and very narrow distribution of molecular weight was obtained (polydispersity index less than 1.2). The FT-IR and NMR results show that the 8-hydroxyquinloine group was chemically bonded to the polymer end and there is nearly one 8-hydroxyquinoline group in per polymer chain. All those data show that polymerization of styrene at such conditions displayed living characters. The polymer with 8-hydroxyqquinoline end group reacted with triethylaluminum to form polymeric light-emitting complex and single layer LED was prepared by common spin-coating method. The peak wavelength of LED based on synthesized polymeric complex was around 570 nm.     

Selective dynamic serialization for reducing energy consumption in hardware transactional memory systems

In the search for new paradigms to simplify multithreaded programming, Transactional Memory (TM) is currently being advocated as a promising alternative to deadlock-prone lock-based synchronization. In this way, future many-core CMP architectures may need to provide hardware support for TM. On the other hand, power dissipation constitutes a first class consideration in multicore processor designs. In this work, we propose Selective Dynamic Serialization (SDS) as a new technique to improve energy consumption without degrading performance in applications with conflicting transactions by avoiding wasted work due to aborted transactions. Our proposal, which is implemented on top of a hardware transactional memory (HTM) system with an eager conflict management policy, detects and serializes conflicting transactions dynamically (at run-time). In its simplest form, in case of conflict, one transaction is allowed to continue whilst the rest are completely stalled. Once the executing transaction has finished, it wakes up several of the stalling transactions. More elaborated implementations of SDS try to delay this behavior until serialization of transactions is profitable, achieving the best trade-off between performance, energy savings and network traffic. SDS implementations differ from each other in the condition that triggers the serialization mode. We have evaluated several SDS schemes using GEMS, a full-system simulator implementing the LogTM-SE Eager–Eager HTM system, and several benchmarks from the STAMP suite. Results for a 16-core CMP show that SDS obtains reductions of 6 % on average in energy consumption (more than 20 % in high contention scenarios) in a wide range of benchmarks without affecting, on average, execution time. At the same time, network traffic level is also reduced by 22 %.     

A new dynamic Bayesian network approach for determining effective connectivity from fMRI data

Two techniques based on the Bayesian network (BN), Gaussian Bayesian network and discrete dynamic Bayesian network (DBN), have recently been used to determine the effective connectivity from functional magnetic resonance imaging (fMRI) data in an exploratory manner and to provide a new method for exploring the interactions among brain regions. However, Gaussian BN ignores the temporal relationships of interactions among brain regions, while discrete DBN loses a great deal of information by discretizing the data. To overcome these limitations, the current study proposes a new BN method based on Gaussian assumptions, termed Gaussian DBN, to capture the temporal characteristics of connectivity with less associated loss of information. A set of synthetic data were generated to measure the robustness of this method to noise, and the results were compared with discrete DBN. In addition, real fMRI data obtained from twelve normal subjects in the resting state was used to further demonstrate and validate the effectiveness of the Gaussian DBN method. The results demonstrated that the Gaussian DBN was more robust than discrete DBN and an improvement over BN.     

Leave-one-out cross-validation-based model selection for multi-input multi-output support vector machine

As an effective approach for multi-input multi-output regression estimation problems, a multi-dimensional support vector regression (SVR), named M-SVR, is generally capable of obtaining better predictions than applying a conventional support vector machine (SVM) independently for each output dimension. However, although there are many generalization error bounds for conventional SVMs, all of them cannot be directly applied to M-SVR. In this paper, a new leave-one-out (LOO) error estimate for M-SVR is derived firstly through a virtual LOO cross-validation procedure. This LOO error estimate can be straightway calculated once a training process ended with less computational complexity than traditional LOO method. Based on this LOO estimate, a new model selection methods for M-SVR based on multi-objective optimization strategy is further proposed in this paper. Experiments on toy noisy function regression and practical engineering data set, that is, dynamic load identification on cylinder vibration system, are both conducted, demonstrating comparable results of the proposed method in terms of generalization performance and computational cost.     

耐盐性树脂PAA的合成及应用研究

以丙烯酸-丙烯酰胺为单体，过硫酸钾为引发剂，N，N-亚甲基双丙烯酰胺为交联剂。水浴阶梯升温共聚合成耐盐性树脂，采用正交试验通过分析，研究了主要因素对产物性能的影响，确定较佳反应条件：T=50℃(2h)～65℃(3h)，单体配比nAM：nAA=1：11，单体中和度[N]=90％～95％。引发剂浓度[I]=0．3％，单体浓度[M]=30％～35％，交联剂浓度[C]=0．025％～0．03％，并将此树脂作为缓释剂应用于固载二氧化氯中，取得了良好的效果。     

振动剪切作用下聚合物熔体的非仿射网络结构模型——振动参数对聚合物熔体黏性的影响

利用非仿射网络结构本构模型分析了正弦脉动流场中振动参数对聚合物熔体黏性的影响作用，并从缠结密度的概念上来解释其影响规律。