传播游戏与选择聚神:电影解说短视频对用户观看原片意愿的影响

近几年,短视频平台涌现出大量电影解说类短视频,这些短视频用几分钟到十几分钟就可以讲完一部影视剧情节。这在社会生活节奏加速的时代背景下,能够帮助用户快速筛选有价值的电影信息,促成观影行为的产生。本文通过整合技术接受模型和信息采纳模型,并在传播游戏理论的视角下提出视频趣味性和观影偏好匹配两个变量,构建影响用户观看电影原片意愿的理论模型,并在多元回归分析法的指导下,对通过在线调查获得的959名观看者数据进行检验和讨论,验证了传播游戏理论对于“选择聚神”概念的解释力。以此为影视传媒单位创新影片推广路径、盘活已有影视剧资源提供有益的理论参照和可行建议。

线索贯穿 形聚神凝

牵挂是一种思念，牵挂是一种情谊，牵挂也是一种幸福。父母时儿女的牵挂是一份深深的爱：朋友对我们的牵挂是一份浓浓的关心；你的心中也许也会积存一份牵挂，梦萦魂牵。心中有牵挂，是一种拥有；爱人所牵挂，是一种收获。你对牵挂又有怎样的体会？

党的建设制度改革的五维目标体系与实现路径

怎样把握好党的建设制度改革的正确政治方向,确立什么样的改革基本目标,选择什么样的实现路径,是事关党的建设制度改革能否取得成效的首要问题。深化党的建设制度改革的基本目标,不是单一的,而是一个多维度多层次的任务目标体系。实现这些基本目标,关键在聚焦、聚神、聚力抓好落实。

EFFECTIVE FEATURE ANALYSIS FOR COLOR IMAGE SEGMENTATION

An approach for color image segmentation is proposed based on the contributions of color features to segmentation rather than the choice of a particular color space. The determination of effective color features depends on the analysis of various color features from each tested color image via the designed feature encoding. It is different from the pervious methods where self organized feature map (SOFM) is used for constructing the feature encoding so that the feature encoding can self organize the effective features for different color images. Fuzzy clustering is applied for the final segmentation when the well suited color features and the initial parameter are available. The proposed method has been applied in segmenting different types of color images and the experimental results show that it outperforms the classical clustering method. The study shows that the feature encoding approach offers great promise in automating and optimizing the segmentation of color images.

凝聚课堂之“神”

把握课堂的独学、交流、展示三个环节,注意过程中细节的培养,凝聚课堂之"神",使学生真正获得有效的学习效果。

Study on Pests Forecasting Using the Method of Neural Network Based on Fuzzy Clustering

Aimed to the characters of pests forecast such as fuzziness, correlation, nonlinear and real-time as well as decline of generalization capacity of neural network in prediction with few observations, a method of pests forecasting using the method of neural network based on fuzzy clustering was proposed in this experiment. The simulation results demonstrated that the method was simple and practical and could forecast pests fast and accurately, particularly, the method could obtain good results with few samples and samples correlation.

DNA Sequence Classification Based on the Side Chain Radical Polarity of Amino Acids

The features of DNA sequence fragments were extracted from the distribution density of the condons in the individual cases of DNA sequence fragments. Based on the polarity of side chain radicals of amino acids molecules, the amino acids were classified into five categories, and the frequencies of these five categories were calculated. This kind of feature extraction based on the biological meanings not only took the content of basic groups into consideration, but also considered the marshal ing sequence of the basic groups. The hierarchical clustering analysis and BP neural network were used to classify the DNA sequence fragments. The results showed that the classification results of these two kinds of algo-rithms not only had high accuracy, but also had high consistence, indicating that this kind of feature extraction was superior over the traditional feature extraction which only took the features of basic groups into consideration.

Polyglutamine toxicity in non-neuronal cells

The neurodegenerative polyglutamine diseases are caused various disease proteins. Although these mutant proteins are by an expansion of unstable polyglutamine repeats in expressed ubiquitously in neuronal and non-neuronal cells, they cause selective degeneration of specific neuronal populations. Recently, increasing evidence shows that polyglutamine disease proteins also affect non-neuronal cells. However, it remains unclear how the expression of polyglutamine proteins in non-neuronal cells contributes to the course of the polyglutamine diseases. Here, we discuss recent findings about the expression of mutant polyglutamine proteins in non-neuronal cells and their influence on neurological symptoms. Understanding the contribution of non-neuronal polyglutamine proteins to disease progres- sion will help elucidate disease mechanisms and also help in the development of new treatment options.

Dynamic vaccine distribution model based on epidemic diffusion rule and clustering approach

Due to the fact that the emergency medicine distribution is vital to the quick response to urgent demand when an epidemic occurs, the optimal vaccine distribution approach is explored according to the epidemic diffusion rule and different urgency degrees of affected areas with the background of the epidemic outbreak in a given region. First, the SIQR （susceptible, infected, quarantined,recovered） epidemic model with pulse vaccination is introduced to describe the epidemic diffusion rule and obtain the demanded vaccine in each pulse. Based on the SIQR model, the affected areas are clustered by using the self-organizing map （SOM） neutral network to qualify the results. Then, a dynamic vaccine distribution model is formulated, incorporating the results of clustering the affected areas with the goals of both reducing the transportation cost and decreasing the unsatisfied demand for the emergency logistics network. Numerical study with twenty affected areas and four distribution centers is carried out. The corresponding numerical results indicate that the proposed approach can make an outstanding contribution to controlling the affected areas with a relatively high degree of urgency, and the comparison results prove that the performance of the clustering method is superior to that of the non-clustering method on controlling epidemic diffusion.

EFFECT OF ERYTHROMYCIN ON GASTRIC DYSMOTILITY AND NEUROENDOCRINE PEPTIDES IN RATS WITH DIABETES MELLITUS

Objective To investigate the effect of erythromycin on the contractive activity of the isolated gastric antrum smooth muscle and somatostatin （SS）, vasoactive intestinal peptide （VIP）, motilin （MTL）, and substance P （SP） in plasma and isolated gastric antrum tissue of diabetes mellitus （DM） rat models. Methods Thirty male Sprague-Dawley rats were divided into three groups： control group （n = 10）, DM group （n = 10）, and erythromycin group （DM models with erythromycin treatment, n = 10）. A single dose of streptozotocin （100 mg/kg, dissolved in 0. I mol/L citric acid buffer, pH4.5） was injected intraperitoneally. After 48 to 72 hours, rats with blood glucose above 16.7 mmol/L and urine glucose level to be （＋＋＋ ） to （＋＋＋＋） over one week were considered successful DM models. The resting tension, mean contractile amplitude and fi＇equency of spontaneous change in isolated longitudinal and circular gastric antrum smooth muscle strips were measured. SS, VIP, MTL, and SP levels in plasma and gastric antrum tissue were measured using radioimmunoassay. Results （1） In the isolated gastric antrum smooth muscle strips, the gastric motility parameters were lower in DM group than those in control group except circular smooth muscle contractile amplitude and longitudinal smooth muscle contractile fi＇equency. The gastric motility parameters were significantly strengthened in erythromycin group, compared with DM group except longitudinal smooth muscle resting tension （P 〈 0.01 ）. （2） Plasma SS, VIP, and MTL concentrations in DM group were higher than those in control （P 〈 0.05）, while the SP level decreased （P 〈 0.05）. In the gastric antrum, SS of DM group was significantly higher than that of control group （P 〈 0.01 ）, while SP and MTL levels were lower than those of control group （P 〈 0.05 and P 〈 0.01, respectively）. However, the level of VIP in gastric antrum tissue did not change among three groups. The plasma level of SS in erythromycin group was higher than that of DM group （P 〈 0.05）. （3） The blood glucose was lower in erythromycin group than DM group （P 〈 0.01 ）. Conclusions Erythromycin has direct effects on contractive activity of gastric smooth muscle in diabetic rats, but there are few effects on neuroendocrine peptides. Gastric-motility disorders in diabetic rats have a correlation with the changes of neuroendocrine peptide levels in plasma and gastric antrum tissue.

Clustering in mobile ad hoc network based on neural network

An on-demand distributed clustering algorithm based on neural network was proposed. The system parameters and the combined weight for each node were computed, and cluster-heads were chosen using the weighted clustering algorithm, then a training set was created and a neural network was trained. In this algorithm, several system parameters were taken into account, such as the ideal node-degree, the transmission power, the mobility and the battery power of the nodes. The algorithm can be used directly to test whether a node is a cluster-head or not. Moreover, the clusters recreation can be speeded up.

Clustering-based selective neural network ensemble

An effective ensemble should consist of a set of networks that are both accurate and diverse. We propose a novel clustering-based selective algorithm for constructing neural network ensemble, where clustering technology is used to classify trained networks according to similarity and optimally select the most accurate individual network from each cluster to make up the ensemble. Empirical studies on regression of four typical datasets showed that this approach yields significantly smaller en- semble achieving better performance than other traditional ones such as Bagging and Boosting. The bias variance decomposition of the predictive error shows that the success of the proposed approach may lie in its properly tuning the bias/variance trade-off to reduce the prediction error (the sum of bias2 and variance).

Antigenicity and Hemaglutination Activity of a Recombinant Hemagglutinin-Neuraminidase of Paramyxovirus Tianjin Strain

Paramyxovirus Tianjin strain, a new genotype of Sendai virus, was isolated from the lungs of common cotton-eared marmoset that died of severe respiratory infection in the marmoset colonies. The 19.28% IgM positive rate in the young children with acute respiratory tract infection suggested a close relationship between Tianjin strain and humans. Hemagglutinin-neuraminidase (HN) is its major transmembrane glycoprotein responsible for viral attachment, penetration and release. To clear the relationship between HN structure and function of paramyxovirus Tianjin strain, rHN1, rHN2 and rHN3 overlapping the ectodomain of HN protein were expressed. Their antigenicity and hemaglutination activity, as well as cross reactivity to standard antisera against influenza virus type A, type B were analyzed. The results indicated expressed rHNs have the natural antigenicity. The segment rHN2 possesses more linear epitopes exposed on the surface of the native HN protein than found in segments rHN3 and rHN1. The hemagglutination activity of segment rHN3 is higher than that of segments rHN2 and rHN1, and partially dependent on the three-dimensional conformation of HN3 protein. Cross-reactivity between rHNs and standard antisera against influenza virus type A, type B suggested that rHNs might not be the best alternative as specific antigens to detect virus in clinical serum specimens.

Possible Role of Mast Cells and Neuropeptides in the Recovery Process of Dextran Sulfate Sodium-induced Colitis in Rats

Objective To clarify the role of mast cells and neuropeptides substance P （SP）, somatostatin （SS）, and vasoactive intestinal peptide （VIP） in dextran sulfate sodium （DSS）-induced colitis in rats. Methods Experimental colitis was induced in Sprague-Dawley rats （180-200 g, n=20） by oral in- gestion of 4% （w/v） DSS in drinking water for 7 days. Control rats （n=5） drank water and were sacrificed on day 0. Mast cell number, histamine levels in whole blood and tissue, tissue levels of SP, SS and, VIP in the dis- tal colon of the rats were measured on day 8, day 13, and day 18 of experimentation. Results Oral administration of 4% DSS solution for 7 days resulted in surface epithelial loss and crypt loss in the distal colon. Mast cell count increased on day 8 （1.75±1.09/mm vs. 0.38±0.24/mm, P〈0.05） and day 13 （1.55±1.01/mm vs. 0.38±0.24/mm, P〈0.05） after DSS treatment. Whole blood his- tamine levels were increased on day 8 （266.93±35.62 ng/mL vs. 76.87±32.28 ng/mL, P〈0.01） and gradu- ally decreased by clay 13 and day 18 after DSS treatment. Histamine levels in the distal colon were decreased on day 8 （1.77±0.65 ng/mg vs. 3.06±0.87 ng/mg, P〈0.05） and recovered to control levels by day 13 after DSS treatment. SP level in the distal colon gradually increased and were raised significantly by day 13 （8777.14±3056.14 pg/mL vs. 4739.66±3299.81 pg/mL, P〈0.05） after DSS treatment. SS and VIP levels in the distal colon were not changed. Conclusions Mast cell degranulation followed by histamine release may play an important role in the pathogenesis of colitis induced by DSS. SP may be a significant substance in the progression of inflamma- tion and the recovery process of DSS-induced colitis.

Melt Index Prediction by Neural Soft-Sensor Based on Multi-Scale Analysis and Principal Component Analysis

Prediction of melt index （MI）, the most important parameter in determining the product＇s grade and quality control of polypropylene produced in practical industrial processes, is studied. A novel soft-sensor model with principal component analysis （PCA）, radial basis function （RBF） networks, and multi-scale analysis （MSA） is proposed to infer the MI of manufactured products from real process variables, where PCA is carried out to select the most relevant process features and to eliminate the correlations of the input variables, MSA is introduced to a^quire much more information and to reduce the uncertainty of the system, and RBF networks are used to characterize the nonlinearity of the process. The research results show that the proposed method provides promising prediction reliability and accuracy, and supposed to have extensive application prospects in propylene polymerization processes.

Simple pain measures reveal psycho-social pathology in patients with Crohn's disease

To determine whether pain has psycho-social associations in adult Crohn’s disease (CD) patients.METHODSPatients completed demographics, disease status, Patient Harvey-Bradshaw Index (P-HBI), Short Form Health Survey (SF-36), Short Inflammatory Bowel Disease Questionnaire (SIBDQ), and five socio-psychological questionnaires: Brief Symptom Inventory, Brief COPE Inventory, Family Assessment Device, Satisfaction with Life Scale, and Work Productivity and Activity Impairment Questionnaire. Pain sub-scales in P-HBI, SF-36 and SIBDQ measures were recoded into 4 identical scores for univariate and multinomial logistic regression analysis of associations with psycho-social variables.RESULTSThe cohort comprised 594 patients, mean age 38.6 ± 14.8 years, women 52.5%, P-HBI 5.76 ± 5.15. P-HBI, SF-36 and SIBDQ broadly agreed in their assessment of pain intensity. More severe pain was significantly associated with female gender, low socio-economic status, unemployment, Israeli birth and smoking. Higher pain scores correlated positively with psychological stress, dysfunctional coping strategies, poor family relationships, absenteeism, presenteeism, productivity loss and activity impairment and all WPAI sub-scores. Patients exhibiting greater satisfaction with life had less pain. The regression showed increasing odds ratios for psychological stress (lowest 2.26, highest 12.17) and female gender (highest 3.19) with increasing pain. Internet-recruited patients were sicker and differed from hardcopy questionnaire patients in their associations with pain.CONCLUSIONPain measures in P-HBI, SF-36 and SIBDQ correlate with psycho-social pathology in CD. Physicians should be aware also of these relationships in approaching CD patients with pain.

Evolution of two properties for scale-free network

Fitness of node can denote its competing power and clustering denotes the transitivity of network. Because the fitness of node is uncertain or fuzzy in some social networks, an explicit form of the degree distribution on fuzzy fitness is derived within a mean field approach. It is a weighted sum of different fuzzy fitness. It can be found that the fuzzy fitness of nodes may lead to multiscaling. Moreover, the clustering coefficient of node decays as power law and clustering coefficient of network behavior not-decrease-but-increase’ phenomenon after some time. Some computer simulation results of these models illustrate these analytical results.

Turnout fault prediction method based on gated recurrent units model

Turnout is one of the important signal infrastructure equipment,which will directly affect the safety and efficiency of driving.Base on analysis of the power curve of the turnout,we extract and select the time domain and Haar wavelet transform characteristics of the curve firstly.Then the correlation between the degradation state and the fault state is established by using the clustering algorithm and the Pearson correlation coefficient.Finally,the convolutional neural network(CNN)and the gated recurrent unit(GRU)are used to establish the state prediction model of the turnout to realize the failure prediction.The CNN can directly extract features from the original data of the turnout and reduce the dimension,which simplifies the prediction process.Due to its unique gate structure and time series processing features,GRU has certain advantages over the traditional forecasting methods in terms of prediction accuracy and time.The experimental results show that the accuracy of prediction can reach 94.2%when the feature matrix adopts 40-dimensional input and iterates 50 times.

Modified imperialist competitive algorithm-based neural network to determine shear strength of concrete beams reinforced with FRP

Fiber reinforced polymers (FRPs), unlike steel, are corrosion-resistant and therefore are of interest;however, their use is hindered because their brittle shear is formulated in most specifications using limited data available at the time. We aimed to predict the shear strength of concrete beams reinforced with FRP bars and without stirrups by compiling a relatively large database of 198 previously published test results (available in appendix). To model shear strength, an artificial neural network was trained by an ensemble of Levenberg-Marquardt and imperialist competitive algorithms. The results suggested superior accuracy of model compared to equations available in specifications and literature.

A Scientific Study on the Holy Spiritual Descending in NRMs of Korea： Focus upon the Paranormal Phenomena of the Holy Spirit by the Victor

The limit and the problem of modern religion and science are due to the materialistic, mechanistic, and dichotomous thought that separates humanity from God, spirit from body and I from you. Indicating that the methodology is wrong, the author will suggest an alternative to solve its problem. In the body, the author will introduce the paranormal phenomena focusing on the descending of the Holy Spirit by the Victor on NRMs in Korea. The author will speak of the differences between Aura and the light of the Holy Spirit using some new methodologies of participant observation by film photo-graphing and interviewing testimonies from fieldwork. Furthermore the author attempted to research scientifically how the light of life emitted from the Victor influences humanity and all things. The author will tell the theory of bio scientific and biblical salvation and immortality based on somatic. This paper will contribute in revealing the invisible God and the Holy Spirit to be physically seen.