一位具有人情味的物理大师——读《人情物理杨振宁》

科学家,在一些人的眼里,总认为是不食人间烟火的人.其实不然,他们也有情,也有义.由香港大公报副总编叶中敏女士撰写的<人情物理杨振宁>里的传主就是一位具有人情味的物理大师.现年81岁的诺贝尔奖金获得者扬振宁为世界科学事业的发展做出了突出贡献,成为继爱因期坦、狄拉克之后20世纪著名的物理学家之一.作者在书中不但叙述了杨振宁的求学经历、科学贡献和学术成就,而且还叙述了杨振宁的亲情、师情和友情以及对中国的深厚感情.读完传记,一股暖流涌上心头,一位具有浓郁人情味的大科学家仿佛就出现在我的眼前.

Emotional speaker recognition based on prosody transformation

A novel emotional speaker recognition system （ESRS） is proposed to compensate for emotion variability. First, the emotion recognition is adopted as a pre-processing part to classify the neutral and emotional speech. Then, the recognized emotion speech is adjusted by prosody modification. Different methods including Gaussian normalization, the Gaussian mixture model （GMM） and support vector regression （SVR） are adopted to define the mapping rules of F0s between emotional and neutral speech, and the average linear ratio is used for the duration modification. Finally, the modified emotional speech is employed for the speaker recognition. The experimental results show that the proposed ESRS can significantly improve the performance of emotional speaker recognition, and the identification rate （IR） is higher than that of the traditional recognition system. The emotional speech with F0 and duration modifications is closer to the neutral one.

A novel speech emotion recognition algorithm based on combination of emotion data field and ant colony search strategy

In order to effectively conduct emotion recognition from spontaneous, non-prototypical and unsegmented speech so as to create a more natural human-machine interaction; a novel speech emotion recognition algorithm based on the combination of the emotional data field （EDF） and the ant colony search （ACS） strategy, called the EDF-ACS algorithm, is proposed. More specifically, the inter- relationship among the turn-based acoustic feature vectors of different labels are established by using the potential function in the EDF. To perform the spontaneous speech emotion recognition, the artificial colony is used to mimic the turn- based acoustic feature vectors. Then, the canonical ACS strategy is used to investigate the movement direction of each artificial ant in the EDF, which is regarded as the emotional label of the corresponding turn-based acoustic feature vector. The proposed EDF-ACS algorithm is evaluated on the continueous audio）＇visual emotion challenge （AVEC） 2012 dataset, which contains the spontaneous, non-prototypical and unsegmented speech emotion data. The experimental results show that the proposed EDF-ACS algorithm outperforms the existing state-of-the-art algorithm in turn-based speech emotion recognition.

Cognitive Emotion Model for Eldercare Robot in Smart Home

Based on the smart home and facial expression recognition, this paper presents a cognitive emotional model for eldercare robot. By combining with Gabor filter, Local Binary Pattern algorithm(LBP) and k-Nearest Neighbor algorithm(KNN) are facial emotional features extracted and recognized. Meanwhile, facial emotional features put influence on robot's emotion state, which is described in AVS emotion space. Then the optimization of smart home environment on the cognitive emotional model is specially analyzed using simulated annealing algorithm(SA). Finally, transition probability from any emotional state to a state of basic emotions is obtained based on the cognitive reappraisal strategy and Euclidean distance. The simulation and experiment have tested and verified the effective in reducing negative emotional state.

Artificial emotional model based on finite state machine

According to the basic emotional theory, the artificial emotional model based on the finite state machine（FSM） was presented. In finite state machine model of emotion, the emotional space included the basic emotional space and the multiple emotional spaces. The emotion-switching diagram was defined and transition fimction was developed using Markov chain and linear interpolation algorithm. The simulation model was built using Stateflow toolbox and Simulink toolbox based on the Matlab platform. And the model included three subsystems： the input one, the emotion one and the behavior one. In the emotional subsystem, the responses of different personalities to the external stimuli were described by defining personal space. This model takes states from an emotional space and updates its state depending on its current state and a state of its input （also a state-emotion）. The simulation model realizes the process of switching the emotion from the neutral state to other basic emotions. The simulation result is proved to correspond to emotion-switching law of human beings.

Detection of artificial pornographic pictures based on multiple features and tree mode

It is easy for teenagers to view pornographic pictures on social networks. Many researchers have studied the detection of real pornographic pictures, but there are few studies on those that are artificial. In this work, we studied how to detect artificial pornographic pictures, especially when they are on social networks. The whole detection process can be divided into two stages： feature selection and picture detection. In the feature selection stage, seven types of features that favour picture detection were selected. In the picture detection stage, three steps were included. 1） In order to alleviate the imbalance in the number of artificial pornographic pictures and normal ones, the training dataset of artificial pornographic pictures was expanded. Therefore, the features which were extracted from the training dataset can also be expanded too. 2） In order to reduce the time of feature extraction, a fast method which extracted features based on the proportionally scaled picture rather than the original one was proposed. 3） Three tree models were compared and a gradient boost decision tree （GBDT） was selected for the final picture detection. Three sets of experimental results show that the proposed method can achieve better recognition precision and drastically reduce the time cost of the method.

Application of rational emotive behavior therapy in patients with colorectal cancer undergoing adjuvant chemotherapy

Objective:This study aimed to explore the effects of our rational emotive behavior therapy(REBT)program on symptoms,anxiety,depression,and sleep state in patients with colorectal cancer(CRC)undergoing chemotherapy.Methods:From October 2020 to May 2021,fifty-six patients with CRC in a hospital in the Hunan Province were randomly divided into an intervention group(n=28)and a control group(n=28).The patients in the intervention group completed a 6-week REBT program based on routine nursing care,including four courses:1)establish a relationship and formulate health files;2)group communications and study symptom management;3)continuously provide health knowledge and strengthen healthy behavior;and 4)review the treatment and summary.The control group maintained routine nursing care.The simplified Chinese version of the Memorial Symptom Assessment Scale Short Form(MSASeSFeSC),the Hospital Anxiety and Depression Scale(HADS),and the Pittsburgh Sleep Quality Index(PSQI)scale were used to investigate and compare the intervention effects of the two groups at baseline(T1,before the intervention),four weeks(T2),and six weeks(T3)after the intervention.Results:The intervention group was significantly improved in symptoms,anxiety,depression,and sleep state,compared with the control group.At T2,MSASeSFeSC(24.43±4.26 vs.28.07±3.91),symptom distress(17.29±4.04 vs.19.39±3.59),symptom frequency(7.14±1.51 vs.8.68±1.42),HADS(13.68±3.38 vs.15.86±3.79),anxiety(3.89±1.85 vs.5.18±2.18),and depression(9.79±2.06 vs.10.68±2.23),showed that the difference between the two groups was statistically significant(P<0.05).At T3,MSASeSFeSC(23.89±3.54 vs.30.14±3.94),symptom distress(17.61±3.52 vs.21.32±3.57),symptom frequency(6.29±1.49 vs.8.82±1.47),HADS(11.82±2.57 vs.16.29±3.13),anxiety(3.21±1.64 vs.5.61±1.77),and depression(8.61±1.52 vs.10.68±1.81),showed that the difference between the two groups was statistically significant(P<0.05).The sleep state of the intervention group was better than the control group at T3,with decreased score of PSQI[4.00(3.00,8.00)vs.9.00(7.00,12.50),Z=-3.706,P<0.001].Conclusion:The 6-week REBT program can effectively improve the symptom,anxiety,depression,and sleep state of patients with CRC undergoing chemotherapy,which could as a care plan for patients with CRC who are repeatedly admitted to the hospital for chemotherapy.

The realization of interpersonal function with formulaic language

Language plays an important role in interpersonal communication, among which the importance of formulaic language shall never be under-estimated. Reflected in not only the language of individual language users but also language community, formulaic language could help establish and maintain human relationships. Meanwhile, interpersonal function is the most important one among the three metafunctions of language. The present paper aims to find the interface between functional grammar and the study of formulaic language, and consequently the significance of formulaic language in the realization of interoersonal function.

Emotional State Transition Model Based on Stimulus and Personality Characteristics

In order to use mathematical methods to study how cognitive reappraisal strategies affect the output state of emotions,Gross's cognitive reappraisal strategy is transformed into a quantitative parameter which is proposed to describe the general perception of emotional events on the basis of the emotion regulation.According to Gross's emotional regulation model,the Finite State Machine(FSM) model is used for describing the process of emotional state transition and the Likert 5 grading scale is introduced to study the level of an individual's reappraisal according to the participant's self-evaluation.The experimental results verify that the algorithm can effectively describe the relationship between the reappraisal strategy,emotional events and an emotiongenerative process.There are multiple dimensions of a human's emotional state.Thus,in the field of human-computer interaction,further research requires the development of a specific algorithm which can be implemented by a computer for the emotion regulation process.

The expression significance and associativity of ILK and PTEN in gastric cancer tissue

Objective: To research the contribution of ILK and PTEN to the carcinogenesis and development of gastric carcinoma and the relation with anti-oncogene PTEN. Methods: ILK and PTEN proteins, PTEN mRNA of 76 cases of normal gastric mucous and 112 cases of gastric carcinoma were detected by immunohistochemistry method and in situ hybridization. Results: The expression of ILK, PTEN protein in gastric carcinoma group and normal gastric mucosa group, muscular layer invasive group and no muscular layer invasive group, lymphatic metastasis group and non-lymphatic metastasis group were all statistical significance (P < 0.05 or P< 0.01). The expression of PTEN mRNA of gastric carcinoma group was lower than that of normal gastric mucosa group (P < 0.01). The expression of ILK and PTEN protein had negative correlation (r = -0.347, P < 0.01). Conclusion: ILK protein increasing and PTEN protein decreasing have closely relation with the genesis and development of gastric carcinoma, and controlling them may become a new treating target gastric cancer.

月读

人情、面子与权力的再生产，当中国改变世界。

A Study on Chinese English Leamers＇ Use of Emotion Words

Most educated Chinese take English as an important communication tool and the language has been increasingly frequently used in all walks of life in the country. This paper is to examine the use of English emotion words on the target group of English learners in China. The study is designed to find out the relationship between the use of emotion words and such relevant variables as language proficiency, gender, and age. The results demonstrate that the use of emotion words is significantly linked to the level of proficiency as well as gender. Age is found to have slight effect on the use of emotion words. The study also reveals that more positive emotion words are produced than negative ones in the speech. Based on the major findings, some implications and suggestions are offered： Firstly, English learners in China are expected to improve their language proficiency, particularly that of listening and speaking. Secondly, they are supposed to enhance their culture awareness of English by means of exposing themselves to as much authentic language as possible.

Facial Robot Expression Simulator(FRESi)——A Simulator to Implement Dynamic Facial Expression

Most of the robots are nowadays evolving and imitating huiron social skills to achieve sociable interaction with humanas. Socially interactive robots require different characteristics than conventional robots. Likewise human-human interaction, human-robot interaction is also accompanied with emotional interaction. Therefore, the robot＇s emotional expression is very important for human, especially facial expressions play an important role among the whole part of the human body. In this paper, we introduce a facial robot expression simulator FRESi.

Awakening from genuine love in Lady Chatterley＇s lover

Both D. H. Lawrence and his novel Lady Chatterley＇s lover are sometimes prejudicially associated in the minds of the general public with pornography. Yet after meditative reading, we find that Lawrence, through revelation of Connie＇s gradual awakening from genuine love, has made his utmost effort to explore possible solutions to harmonious androgyny between men and women so as to revitalize the distorted human nature caused by the industrial civilization.

作文评分：到语言为止？——就作文评分与黄助昌先生商榷兼谈作文的道德底线

《中学语文》2006年第12期上半月“教学大参考”上黄助昌先生《作文评分：到语言为止》一文，表达了这样的作文评分观点：“作文是对学生语言能力的考查，并非对学生作政治鉴定，所以应当回归到作文本体，作文评分也就应当以语言能力为标准，且只能到语言为止。”接着以美国11岁男孩萨拉．邓肯的获奖文章《自由的美国？》、南京金陵中学费滢滢的高考作文《人情与季节》、2005年湖北考生的《出得厅堂入得厨房之王国维可以休矣》和美国学生的一篇主题为《邱吉尔应对二次“世界大战”负责任》的文章为论据，一再表达作文评分应只看语言不看其思想内容的观点。要求“我们要汲取教训并树立这样的观念：‘语言表达’高于一切”：因为黄先生认为．如果顾及作文思想内容即所谓“道”时，就会钳制学生思维，“扼杀学生个性表达”，从而产生“悲剧”。笔者认为这些观点有失偏颇。不是“回归到作文本体”，恰恰是悖离作文本体的。必须予以澄清。

Accurate analysis of ＂Chinese New Standard＂ with the exploration of classical poetry ＂mood＂ Method

The mood is intended to send poetry lyric and a form of expressive, while the Chinese have a long attention of the ＂mood＂ to convey tradition and from the east, we can see the nation＇ s awareness of thinking, oriental poet emphasis of things＇ teaser, expression of mood. Therefore, secondary school teachers in the resolution of the ＂Chinese New Standard＂ in Chinese classical poetry pay attention to poetry with the main objective unity, and the traditional interpretation of metaphor Fu poetry ＂mood.＂

A Brief Tour on Exotic Control Objectives in Robotics

Formulation of control objectives is a key issue in automatic control systems design. Although at first sight the desired goal （control objective） of a control system seems to be a trivial and obvious matter, for effectiveness of some high level robotic tasks, unusual exotic control objectives may be required. This paper presents a review of some exotic control objectives useful in robotics, such as velocity field control objective and range control objective. The paper also proposes a novel confinement control objective. The usefulness of these exotic control objectives may appear in safe robot-human interaction and self-protection of robots against collisions.

Label distribution expression recognition algorithm based on asymptotic truth value

Ambiguous expression is a common phenomenon in facial expression recognition(FER).Because of the existence of ambiguous expression,the effect of FER is severely limited.The reason maybe that the single label of the data cannot effectively describe complex emotional intentions which are vital in FER.Label distribution learning contains more information and is a possible way to solve this problem.To apply label distribution learning on FER,a label distribution expression recognition algorithm based on asymptotic truth value is proposed.Under the premise of not incorporating extraneous quantitative information,the original information of database is fully used to complete the generation and utilization of label distribution.Firstly,in training part,single label learning is used to collect the mean value of the overall distribution of data.Then,the true value of data label is approached gradually on the granularity of data batch.Finally,the whole network model is retrained using the generated label distribution data.Experimental results show that this method can improve the accuracy of the network model obviously,and has certain competitiveness compared with the advanced algorithms.

Border Shifting in Naomi Nye＇s Habibi

This paper investigates how the novel Habibi （1997） by the Arab-American writer Naomi Nye addresses the theme of border shifting from a postmodernist perspective that deconstructs the traditional view of borders meant to maintain exclusion and hegemony and instead considers them as being often flimsy, malleable, and changeable. Drawing upon her experience as a multifarious Arab-American writer whose father was a Palestinian immigrant and whose mother was an American, Nye tries to build bridges across political, national, cultural, and ethnic boundaries. Through a love story between the two protagonists （Liyana, whose father is a Palestinian-American and whose mother is American and Omer, whose parents are Jewish Israelis）, Nye endeavors to bring about a sense of harmony and understanding between the politically, ethnically, culturally, and racially separated J home whether in reality ews and Palestinians. At the end, Liyana＇s family realizes they can have more than one or in imagination.

Bag-of-visual-words model for artificial pornographic images recognition

It is illegal to spread and transmit pornographic images over internet,either in real or in artificial format.The traditional methods are designed to identify real pornographic images and they are less efficient in dealing with artificial images.Therefore,criminals turn to release artificial pornographic images in some specific scenes,e.g.,in social networks.To efficiently identify artificial pornographic images,a novel bag-of-visual-words based approach is proposed in the work.In the bag-of-words(Bo W)framework,speeded-up robust feature(SURF)is adopted for feature extraction at first,then a visual vocabulary is constructed through K-means clustering and images are represented by an improved Bo W encoding method,and finally the visual words are fed into a learning machine for training and classification.Different from the traditional BoW method,the proposed method sets a weight on each visual word according to the number of features that each cluster contains.Moreover,a non-binary encoding method and cross-matching strategy are utilized to improve the discriminative power of the visual words.Experimental results indicate that the proposed method outperforms the traditional method.