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Constructing charge transfer (CT) systems and packing arrangement are common and effective methods to control the efficiency of nonlinear optical (NLO) materials. Apart from the traditional through-bond CT (TBCT) systems, through-space CT (TSCT) also leads to distinctive optical and electronic properties. Meanwhile, corresponding theoretical investigations of the aggregation effect are highly desired. In this work, some TSCT and model compounds incorporating acenaphthene as a scaffold and triphenylamine (TPA) as the donor are theoretically performed to systematically reveal the effect of both solvent and solid environments on their static first hyperpolarizabilities (β

Based on dynamic corrosion experiments, we propose a new model for predicting corrosion rate that is based on an alternating conditional expectation (ACE) algorithm. This model lets us more accurately predict the corrosion rate for a broad range of temperatures, pH, and concentrations of Ca2+, HCO − , Mg2+, Cl–, SO 2 − ions. Based on tests performed on a testing sample group, we have confirmed the reliability of the model and have also demonstrated its high accuracy. Sensitivity analysis based on a rank correlation coefficient revealed that the major factor influencing the corrosion rate of N80 steel is the pH value. We have also carried out a comparison analysis of the results obtained when using the ACE algorithm and the results obtained when using a backpropagation neural network (BPNN) and the support vector regression (SVR) method. As a result, we found that the model based on the ACE algorithm is more accurate than other currently used models.

A new lignan, named ginkgool (1), was isolated from the roots of Ginkgo biloba together with four known lignans, isolariciresinol (2), cycloolivil (3), pinoresinol (4), and sesamin (5). The new lignan was characterized as 4β-(5-hydroxy-3-methoxybenzyl)-2α-(4-hydroxy-3-methoxyphenyl)-3β-(hydroxymethyl)-tetrahydrofuran-4α-ol (1). The structures of the five compounds were determined on the basis of physicochemical and spectrometric data.

To compare the clinical effects of circumcision and the foreskin-deglove plus shaft-fix (FDSF) procedure in the treatment of phimosis or redundant prepuce in obese adult males (body mass index [BMI] ≥ 28 kg/m²).Forty-four obese adult men with phimosis or redundant prepuce underwent circumcision (n = 24) or FDSF (n = 20) according to their own wishes. The patients in the circumcision and FDSF groups were aged (26.38 ± 4.24) and (26.90 ± 3.14) years, with BMIs of (27.77 ± 0.77) and (28.07 ± 2.28) kg/m² and penis lengths of (3.51 ± 0.46) and (3.50 ± 0.59) cm, respectively. The operations were performed under local anesthesia with lidocaine plus ropivacaine mesylate.The operation time of circumcision was (28.04 ± 2.65) min and that of FDSF was (45.45 ± 3.49) min. At 6 months after surgery, normal penile erection was found in all the patients, the penis length was significantly longer in the FDSF than in the circumcision group ([5.01 ± 0.73] vs [3.70 ± 0.47] cm) , and the rate of satisfaction with penile appearance was markedly higher in the former than in the latter group (3.25 ± 0.71 vs 2.83 ± 0.56).The foreskin-deglove plus shaft-fix procedure under local anesthesia with lidocaine and ropivacaine mesylate may achieve desirable penile erection and appearance in the treatment of phimosis or redundant prepuce in obese adult patients.

Sentiment classification has attracted increasing interest from natural language processing. The goal of sentiment classification is to automatically identify whether a given piece of text expresses positive or negative opinion on a topic of interest. This paper presents the standpoint that uses individual model (i-model) based on artificial neural networks (ANNs) to determine text sentiment classification. The individual model consists of sentimental features, feature weight and prior knowledge base. During the training process, i-model that makes right sentimental judgment will correct those are wrong, to make more accurate prediction of text sentiment polarity. Experimental results show that the accuracy of individual model is higher than that of support vector machines (SVMs) and hidden Markov model (HMM) classifiers on movie review corpus.

To enhance the quality of service (QoS) support in IEE 802.11, IEEE 802.11e has been studied, which introduces the so-called hybrid coordination function (HCF). HCF includes two medium access mechanisms: contention-based channel access (EDCA), and contention-free channel access (HCCA). Although IEEE 802.11e has provided differentiated channel access mechanism, when call demand rises for important festivals such as New Year's Day or large scale natural disasters such as earthquakes, the delay of voice will increase and the QoS of voice nodes will drop down rapidly. Through our simulation study, in order to guarantee the QoS of emergency voice calls in congested situation, a higher priority for these calls will be required.

Hybrid peer-to-peer (P2P) system can improve the performance of the entire system using super-peer. But it is difficult to measure a peer''s capability exactly and ensure high reliability of the network. This paper proposes a scheme to solve these problems. Firstly, we present a hybrid P2P network in which the upper layer is Chord network and the lower layer is cluster. Then we provide a strategy to measure a peer''s capability so that a cluster can be organized to be a sorting network in which peers are classified into three types: dynamic-super-node (DSN), backup-node (BN) and ordinary-node (ON). In a cluster, DSN and BNs are strongly connected. And based on this, we present an algorithm DSN flood min (DSNFM) to select DSN BN and maintain consensus of the cluster. Furthermore, we do a reliability analysis of the cluster based on churn rate of the network and gathered three rules of thumb from our simulations.