Showing papers in "Neuroquantology in 2018"

Using a Recurrent Neural Network and Restricted Boltzmann Machines for Malicious Traffic Detection

Abstract: In the studies of intrusion detection/prevention systems (IDS/IPS) and network security situational awareness, malicious traffic detection has been given significantly more attention to prevent malicious traffic. Meanwhile, with the development of machine learning technology, an increasing number of algorithms and models have been employed for attack detection. Previous studies generally used common and typical machine learning models such as SVM, KNN, or a random forest. However, the bottleneck of these types of approaches is two-fold. The input of the model is constructed using the feature engineering method of artificially designed representation, which requires a substantial amounts expertise. Additionally, most detection methods ignore the temporal information between network packets in one micro-flow. In this paper, we regard malicious traffic detection as a classification task and propose a hybrid model that combines a recurrent neural network (RNN) with restricted Boltzmann machines (RBM) which take byte-level raw data as input without feature engineering. Specifically, distributed embedding is utilized to pre-process network data to make it more suitable for deep neural network models. Subsequently, an RBM model is used to extract the feature vectors of the network packets and an RNN model is used to extract the flow feature vector. Finally, the flow vectors are sent to the Softmax layer to obtain the detection result. Experiments based on the ISCX-2012 and DARPA-1998 published datasets show that our proposed RNN-RBM model has a greater detection accuracy, recall rate, and lower false alarm rate than most traditional machine learning models. This proves the effectiveness of the proposed RNN-RBM model in malicious traffic detection.

Research Method Innovation of College Students' Ideological and Political Education Based on Cognitive Neuroscience

Abstract: The innovation of college students’ ideological and political education needs to combine the current situation of education development, follow relevant principles and rules and adjust the principles and mechanisms of education in a timely manner, then make them develop towards a healthy direction. Only through a variety of methods to make the content of ideological and political education into individuals’ mind, can the ideological and political education achieve substantial results. Recently, the systematization and diversification of the research methods of ideological and political education cannot satisfy the requirements of the scientific development of the its research. This paper actively draw on the ideas and methods of natural science and social science research field, the innovation of cognitive neuroscience is applied to college students' ideological and political education research methods, supplied advanced technology and broader research perspective from the aspect of tool provides for the study of the ideological and political education. Accurate and scientific data of the effect of ideological and political education can be obtained through measuring the physiological changes in the specific areas of the human brain by electroencephalography. According to the results of the experiment, we designed more effective education and teaching activities, cleared the educational intervention plan, optimized the plasticity of the brain, and enhanced the effectiveness of ieological and political education.

The Effect of an Emotional Intelligence Intervention on Reducing Stress and Improving Communication Skills of Nursing Students

Abstract: Intensive care units are one of the most anxious environments for its employees, especially for doctors, nurses and nursing students The current study was designed to test the efficacy of an emotional intelligence intervention on reducing stress and improving communication skills of nursing students Nursing student volunteers from an introductory psychology class at a moderate western Chinese university participated for class credit (n=85) We randomly assigned the nursing students to an emotional intelligence group and a control group The sample completed measures of perceived stress and communication skills at baseline and end of study As expected, perceived stress decreased in the emotional intelligence group, but not in the control group, due to the intervention Also, communication skills increased in emotional intelligence group but remained unchanged in the control group Findings suggest that an emotional intelligence intervention can protect nursing students from an increase in perceived stress and a decrease in communication skills in the intensive care units

A Method of Ultrasonic Image Recognition for Thyroid Papillary Carcinoma Based on Deep Convolution Neural Network

Abstract: Thyroid cancer is a malignant tumor that occurs in the thyroid gland and is the most common malignant tumor in the endocrine system. Ultrasound examination is the most important method to diagnose thyroid cancer. The accuracy of ultrasound examination for thyroid cancer is closely related to doctors' cognition and understanding of ultrasound images, and there are subjective judgment and misjudgment. The ultrasound images of thyroid papillary carcinoma are mostly represented by two-dimensional gray scale, and with lower resolution, complicated internal tissue structure, and not obvious features of the cancer, it is difficult to distinguish and diagnose the thyroid papillary carcinoma. In this paper, we introduce the theory of convolution neural network (CNN) in view of the difficulty in recognizing the ultrasound image of thyroid papillary carcinoma, and propose a method which can automatically recognize the ultrasound image of thyroid papillary carcinoma. In terms of the need of ultrasonic image recognition of thyroid papillary carcinoma, the Fast Region-based Convolutional Network method (Faster RCNN) network is improved and normalized by connecting the fourth layer and the fifth layer of the shared convolution layer in the Faster RCNN network. Then, a multi-scale ultrasound image is used at the time of input. Finally, according to the main features of the ultrasound images of thyroid papillary carcinoma, they are classified so as to output detailed ultrasound image diagnosis reports. The experimental results show that compared with the original Faster RCNN network, the proposed method has higher recognition accuracy, shorter training time and higher efficiency in ultrasonic image recognition of thyroid papillary carcinoma.

Electroencephalogram Experiment Based Analysis of Aesthetic Fatigue on Chinese Traditional Garden

Abstract: Traditional Chinese garden is the most significant landscape and tourism resources with high historical value and aesthetic meaning. The sustainable development of tourism resources has homogenized more and more traditional garden resorts where many tourists are attracted to visit at a higher frequency. As a result, it is inevitable for some tourists to generate aesthetic fatigue for these landscapes. This paper launches three rounds of indoor and outdoor tests separately on the four Chinese traditional garden such as Humble Administrator's Garden, the Lingering Garden, the Surging Wave Pavilion and the Lion Grove Garden with electroencephalogram (EEG) technology in attempt to analyze subjective scores of subjects and EEG data. The results reveal some phenomena as landscape playbacks and visits increase: the mean value of EEG attentions declines gradually; the attractiveness of garden photographs to subjects gradually weakens; the novelty, scene abundance, color sensitivity and overall harmonization of four gardens are rated badly, all of which significantly show a phenomenon of aesthetic fatigue. When analyzing the factors affecting the visitors' aesthetic fatigue, we found that the mean value of EEG attentions has a significantly positive correlation with landscape novelty, scene abundance, color sensitivity and overall harmonization when sig <0.05.

Roles of Mindfulness and Perceived Social Support in Mediating the Effect of Psychological Distress on Sleep Quality of College Students

Abstract: This paper aims to disclose the role of mindfulness and perceived social support (PSS) in relationship between psychological distress and sleep quality of college students. For this purpose, 480 questionnaires were issued to students from two colleges in Shaanxi, China. 443 (92.29%) of the questionnaires were returned. Then, the respondents were subject to depression anxiety stress survey (DASS-21), five facet mindfulness questionnaire (FFMQ), the PSS scale (PSSS) and Pittsburgh sleep quality index (PSQI). The main conclusions are as follows: 25.5% of college students had sleep problems and the situation was worse for females; psychological distress had a significant effect on sleep quality and mindfulness, while mindfulness acted as a mediator between psychological distress and sleep quality; the PSS regulated the effect of mindfulness on the sleep quality, and mindfulness partially mediated those with low PSS; the mediation effect of mindfulness was insignificant for those with high PSS, and their sleep quality directly hinged on psychological distress. Therefore, the sleep quality among college students can be improved by promoting their mindfulness and PSS. This research provides new insights into the field of sleep quality.

EEG Classification Based on Sparse Representation and Deep Learning

Abstract: For brain computer interfaces (BCIs) research, the classification of motor imagery brain signals is a major and challenging step. Based on the traditional sparse representation classification, a classification algorithm of electroencephalogram (EEG) based on sparse representation and convolution neural network is proposed by this paper. For the EEG signal, firstly, the features of the signal are obtained through the common spatial pattern (CSP) algorithm, and then the redundant dictionary with sparse representation is constructed based on these features. The sparse representation of the EEG signal is completed and the sparse features can be obtained. Finally, the sparse features are transformed into two dimensional signals, and the convolution neural network is used to complete the classification of EEG signals. Using the dataset downloaded from the website of BCI competition III (dataset IVa), for two types of EEG signals, the experiments show that the recognition accuracy of the method is over 80, and the recognition accuracy is better than that of the traditional SRC algorithm.

Influence Mechanism of Construction Workers' Safety Psychology on their Safety Behavior Based on Event-related Potentials

Abstract: This paper analyzes the causes of the unsafe behavior in construction workers and designs effective management measures Through the identification, observation and investigation of the causes of construction workers' unsafe behavior, the cognitive reason is examined In this paper, an event-related potential (ERP) measurement system consisting of a stimulus generation system (STIM), a signal acquisition and processing system, a subjects response system and a digital amplifier is constructed, and 15 people are tested as experimental subjects in the experimental research The subjects are measured in the aspect of ERP signals before and after the psychological safety The P3a components of the subjects are highest in the frontal area In normal circumstances, P3a appears around 230ms, and the maximum amplitude appears around 270ms Construction workers should subjectively create a healthy and stable psychological environment and control bad mood with rational minds

The Neural Correlates of Celebrity Power on Product Favorableness: An fMRI Study

Abstract: Advertisements featuring celebrities have increased over the years. While we know that the effectiveness of celebrities stems from a transfer of positive affect from celebrity to product, it is still unclear whether celebrities are also able to improve product favorableness in commercials. In the current study, by employing a functional magnetic resonance imaging (fMRI) experiment that presented subjects with a combination of a celebrity face and a car that was familiar to their culture, we investigated the neural correlates of celebrity power on car favorableness in advertising. The results showed that neural activity in brain areas associated with reward, memory, semantics, and attention was higher when viewing a combination of a celebrity face and a car compared to viewing a combination of a non-celebrity face and a car. Furthermore, it was found that the scores of car favorableness were positively correlated with neural activity of left orbitofrontal cortex (OFC), left anterior insula and left higher-order visual cortex in the occipital lobe. This suggests a possible “transfer effect” of positive attitude, and a feeling for the celebrity, while making a preference-judgment for car.

Internalizing behavior disorders symptoms reduction by a social skills training program among Chinese students: A randomized controlled trial

Abstract: Introduction: The primary aim of this study was to evaluate the effectiveness of a social skills training program for Chinese students' internalizing behavior disorders symptoms reduction. Additionally, the study aimed to clarify whether the use of social skills training program would lead to better outcome than the use of daily usual program. Methods: Our RCT study randomly assigned 29 students who were suspected of internalizing behavior disorders to an intervention group in which students received a cognitive- behavioral approach-based social skills training program (n = 16) or to a control group with daily usual program during the period (n = 13). Results: The analyses suggest that students receiving the social skills training program reported a significantly decrease of anxiety, depression and withdrawal symptoms during the end of the intervention and follow-up interval than did students in the control group. Conclusion: cognitive- behavioral approach-based social skills interventions may help increase the sustainability of outcome after treatment for internalizing behavior disorders symptoms.

Space-Time Intervals Underlie Human Conscious Experience, Gravity, and a Theory of Everything

Abstract: Space-time intervals are the fundamental components of conscious experience, gravity, and a Theory of Everything. Space-time intervals are relationships that arise naturally between events. They have a general covariance (independence of coordinate systems, scale invariance), a physical constancy, that encompasses all frames of reference. There are three basic types of space-time intervals (light-like, time-like, space-like) which interact to create space-time and its properties. Human conscious experience is a four-dimensional space-time continuum created through the processing of space-time intervals by the brain; space-time intervals are the source of conscious experience (observed physical reality). Human conscious experience is modeled by Einstein’s special theory of relativity, a theory designed specifically from the general covariance of space-time intervals (for inertial frames of reference). General relativity is our most accurate description of gravity. In general relativity, the general covariance of space-time intervals is extended to all frames of reference (inertial and non-inertial), including gravitational reference frames; space-time intervals are the source of gravity in general relativity. The general covariance of space-time intervals is further extended to quantum mechanics; space-time intervals are the source of quantum gravity. The general covariance of space-time intervals seamlessly merges general relativity with quantum field theory (the two grand theories of the universe). Space-time intervals consequently are the basis of a Theory of Everything (a single all-encompassing coherent theoretical framework of physics that fully explains and links together all physical aspects of the universe). This theoretical framework encompasses our observed physical reality (conscious experience) as well; space-time intervals link observed physical reality to actual physical reality. This provides an accurate and reliable match between observed physical reality and the physical universe by which we can carry on our activity. The Minkowski metric, which defines generally covariant space-time intervals, may be considered an axiom (premise, postulate) for the Theory of Everything.

Relationship between Extraversion and Employees’ Innovative Behavior and Moderating Effect of Organizational Innovative Climate

Abstract: This paper aims to clarify the relationship between extraversion and employees’ innovative and disclose the moderating effect of organizational innovative climate on that relationship. To this end, 300 employees were selected from various enterprises in three Chinese cities, and subjected to a questionnaire survey based on the five factor model (FFM) and 5-point Likert scale. Through statistical regressions, the author explored the effects of extraversion and organizational innovative climate have on employees’ innovative behavior. Then, the organizational innovative climate was divided into five dimensions, and the feature activation theory was implemented to reveal the moderating effect of each dimension on relationship between extraversion and employees’ innovation. Through the above analysis, it is concluded that extraversion has a positive effect on employees’ innovative behavior; the five dimensions of organizational innovative climate all exert a positive effect on employees’ innovative behavior; the resource support in organizational innovative climate has a moderating effect on the relationship between extraversion and employees’ innovation. The research findings shed new light on the improvement of organizational innovative and the construction of an innovative country.

The Epistemological Crisis in Modern Physics

Abstract: In physics today it often happens that experimental data is interpreted as proof of a phenomenon that has not been directly observed, but for which phenomenon there is a theoretical model. With the obtained data acting thereby as proof, the model then becomes recognized as “real,” after which the theoretical phenomenon that the model describes also then becomes recognized as “real” – that is, the heretofore purely theoretical phenomenon is acknowledged as a physical reality, even though it has never been observed, by either instruments or human senses. This relatively new situation, in which unobserved phenomenon come to be treated as if they had been directly observed, has lead modern physics into deep epistemological crisis of which it is not yet aware. The purpose of this article is both to identify the epistemological crisis created by this situation, as well as to present a solution to overcoming this crisis.

Evolution Process of Recycling Chain of Takeout Packages Based on Behavioural Science

Abstract: With the rapid development of the takeout food industry in recent years, the amount of non-degradable wastes such as packing boxes and plastic bags are increasing day by day, which leads to severe waste of resources and pollution of environment. How to deal with the takeout packaging wastes have become a new problem of online ordering and also an important subject of social sustainable development. The construction of a recycling industry chain is an important measure to achieve the recycling of takeout packaging wastes. But this process involves many stakeholders, such as the government, takeout enterprises, package manufacturers and consumers. The cognition and decision of these stakeholders play a decisive role in the construction of the recycling industry chain. An evolutionary game model was established to analyze the effects of different decision behaviours of stakeholders on the construction of the recycling industry chain. And then the MATLAB software was used to dynamically simulate the game system. The results show that in the absence of government intervention, the proportion of the initial decision of consumers and enterprises determines whether the evolutionary game system can converge to the ideal state or not, meanwhile the consumers and enterprises have benign interaction effect in the process of constructing the recycling industry chain; in the case of government intervention, the evolution results of the game system will always reach to the ideal state, and the evolution speed is greatly increased. In the end, the countermeasures and suggestions to optimize the decision behaviours of various stakeholders were provided from the perspective of the government behaviour.

Children’s Landscape Environment Creation Based on Brain Plasticity and Cognition

Abstract: In light of the key role of landscape environment (LE) in children’s growth, the modern children’s LE construction should accommodate the requirements of cultivating the children brain plasticity and cognitive capacity in order to promote the children’s physical and psychological health fundamentally. In this paper, the research method of behaviour analysis-landscape psychology-environment creation was applied. Firstly, the paper analyses the children’s brain plasticity and the behaviour features of cognition, then integrates them with the LE on the basis of the children’s mental activity by behaviour mapping, and finally in terms of landscape planning and design, creates the LE suitable for the children’s brain plasticity and cognition. Besides, this paper studies the LE creation by cultivating the brain plasticity and cognitive capacity: the brain plasticity can be enhanced in 7 aspects: naturality, diversity, interestingness, informatization, artistry, movability and comfort; the cognitive capacity shall be improved in such aspects as differentiation between the cognitive phases, five senses and emotion etc.

Relevance of quantum mechanics in bacterial communication

Abstract: The recent findings confirm that bacteria communicate each other through chemical and electrical signals. Bacteria use chemical signaling molecules which are called as quorum sensing molecules( QSMs) or autoinducers. Moreover, the ion channels in bacteria conduct a long-range electrical signaling within biofilm communities through propagated waves of potassium ions and biofilms attracts other bacterial species too. Both communication process are used by bacteria to make their own survival strategies. In this article, we model this bacterial communication mechanism by complex Ginzburg- Landau equation and discuss the formation of patterns depending on kinematic viscosity associated with internal noise. Again, the potassium wave propagation is described by the non-linear Schrodinger equation in a dissipative environment. By adding perturbation to non-linear Schrodinger equation one arrives at Complex Ginzburg-Landau equation. In this paper we emphasize that at the cellular level(bacteria) we use Complex Ginzburg - Landau equation as a perturbed Non- linear Schrodinger equation to understand the bacterial communication as well as pattern formation in Biofilms for certain range of kinematic viscosity which can be tested in laboratory experiment. Here, the perturbation is due to the existence of non thermal fluctuations associated to the finite size of the bacteria. It sheds new light on the relevance of quantum formalism in understanding the cell to cell communication.

Multi-Sensor Integration Based on a New Quantum Neural Network Model for Land-Vehicle Navigation

Abstract: This paper aims to develop an efficient and accurate multi-sensor integration method for land vehicle navigation. For this purpose, a novel multi-sensor integration model was created based on quantum neural networks (QNNs) and back-propagation training. According to the information interaction mode of biological neurons and the theory on the QNNs, the author firstly put forward a QNN consisting of weighting, aggregation, activation and prompting, and then built a QNN model based on the proposed network. Then, the multi-layer feedforward QNN was combined with back-propagation learning to form a multi-sensor integration approach for land-vehicle navigation. Finally, the efficiency and accuracy of the proposed approach was verified through simulation and field test. This research sheds new light on the integration of data from multiple sensors and the improvement of land-vehicle navigation.

Effect of Risk Preference on Entrepreneurial Cooperative Behavior in Industrial Clusters: Based on Neuromanagement and Event-Related Potentials Experiment

Abstract: The tendency and risk preference of individual behavior affect the cooperative intention and behavior choice of entrepreneurs in industrial clusters. In this study, Event-Related Potentials (ERP) experiment was added to IGT, to investigate the influence of high and low risk preference on the entrepreneur's cooperative behavior. We obtained the related behavioral and ERP data to analyze the entrepreneur's behavior selection. The results showed that there is the greater amplitude of P300 and the smaller amplitude of FRN in high risk preference individuals than that of low risk preference individuals regardless of the feedback of cooperative or non-cooperative behavior words. The t-test results showed that there are the significant differences in the selection ratio and the average response of non-cooperative option were found between the two risk preference types. The non-cooperative behavior intention of high risk preference individuals is higher than that of low risk preference individuals. Therefore, the risk preference has a significant influence on the cooperative behavior intention of entrepreneurs, and the non-cooperative behavior intention of the high risk preference individuals is higher than that of the low risk preference individuals.

The Efficacy of a Transactional Analysis Training Program for Married University Students' Spiritual Intelligence: A Randomized Controlled Study

Abstract: Attention to the various dimensions of intelligence and their role in different psychological, communicational, social and marital processes are becoming widespread and prominent day by day. We conducted a randomized trial in three dispute resolution councils in Xining, western China. We used the scale spiritual intelligence capacity as an indicator of perceived spiritual intelligence and the scale communication skills as an important communication-related outcome variable. The changes in mean spiritual intelligence capacity were significantly higher in the experimental condition than in the control condition. Furthermore, the changes in mean verbal, listening and feedback skills were significantly higher in the experimental condition than in the control condition. An intervention involving transactional analysis training significantly improved perceived spiritual intelligence among married students during the events of life.

Improvement in university students’ critical thinking following a strategic thinking training program

Abstract: Today's experts believe that critical thinking is a major output in higher education and teaching thinking is a basic point to learning. The aim of this study was to explore whether a strategic thinking training program could improve student’s scores on a standardized measure of critical thinking. Sixty-six students aged between 20 and 35 were tested at their college on before the program CCTST and CCTDI. Thirty-nine of these students volunteered to be randomly allocated to the strategic thinking or control group. Students in the strategic thinking group received a strategic thinking training program, but not the students in the control group. The experimental and control groups were then re-tested on CCTST and CCTDI at after the intervention. Students in the strategic thinking group significantly improved their critical thinking skill and critical thinking disposition scores compared to the control group. On average, we observed no group differences between the strategic thinking and control groups. These results have important implications for implementing a strategic thinking training program to protect students from a decrease in critical thinking skill and critical thinking disposition during the achievement of educational goals.

Psychological Mechanism of Adolescent Internet Addiction and Brain Functional Imaging

Abstract: In order to further explore the deep-seated mechanism of adolescent Internet addiction, this study screened out those adolescents with Internet addiction through Young's diagnostic questionnaires revised by Beard and Wolf and conducted multiple personality test questionnaires together with the negative control group, thus analyzing the psychological features of adolescents with Internet addiction. Subsequently, the Barratt Impulsivity Scale (BIS) and GoStop impulse test software are adopted to investigate the relationship between impulsivity and Internet addiction in the experimental group and the control group. It is concluded that the emotional behaviors of adolescents with Internet addiction all present obvious negative features, and Internet addiction is closely related to impulsivity.

Bijective Analysis of Physical Equations and Physical Models

Abstract: A bijective function is a function between the elements of two sets, where each element of one set is paired with exactly one element of the other set, and where each element of the other set is paired with exactly one element of the first set. We can define every physical equation as the set X and the corresponding physical reality that the equation describes as the set Y. Every element in a given equation is an element in the set X, and each element in set X should have exactly one paired element in the set Y. The bijective analysis confirms that Newtonian physics satisfies the bijective function. On the other hand, not all of the equations in the Theory of Relativity satisfy the bijective function. Additionally, the Higgs mechanism does not satisfy the bijective function.

Effect and Mechanism of Total Quality Management on Enterprise Innovation Performance Based on Cognitive Behavior Science

Abstract: From the perspective of cognitive behavior science, the study takes domestic enterprises as samples of empirical research, uses the method of neuroeconomics, and selects 50 healthy quality department heads as paid subjects to voluntarily participate in the experiment to explore the effect and mechanism of TQM (Total Quality Management) on innovation performance In order to explore the direct and indirect effects between TQM and innovation performance, this study introduces knowledge absorptive capacity and environmental dynamics into the relationship between TQM and innovation performance On the basis of maturity scale, 184 valid questionnaires are collected and a statistical analysis is carried out with Lisrel software to validate the hypothesis of this study The results show that: (1) TQM has a direct and positive effect on innovation, and the longer and deeper the implementation of TQM is, the more significant the promotion of innovation is performance However, the resource factors of TQM have no significant effect on innovation performance, which indicates that enterprises implementing TQM strategy do not need to worry about the effect of enterprise size and resources (2) TQM has a significant effect on the knowledge absorptive capacity, which is the key to enterprise innovation (3) In addition to its direct effect on innovation performance, TQM indirectly acts on innovation performance through the intermediary variable of knowledge absorptive capacity, and its mechanism can be divided into direct effect and indirect effect (4) The environmental dynamics faced by enterprises are different, and the effects of TQM on innovation performance are also different Under the high dynamic environment, TQM has no significant effect on innovation, and even has negative effect Under the low dynamic environment, TQM has a very significant effect on innovation (5) TQM and innovation can succeed in an enterprise at the same time, it’s not conflict for enterprises to pursue the quality performance and the enterprise innovation at the same time since two are the key factors to improve the enterprise performance finally

Quantum Mechanics Requires an Observer Context Distinguishing Between Reality and its Mental Representation

Abstract: When phenomena in quantum mechanics are interpreted from the perspective of bio-psychology, wave function collapse from several to a single eigenstate must be plausibly explained. Quantum mechanics requires a context, yet the context of an observer is rarely considered. On the other hand, in bio-psychology, the observer context is examined to explain superposition and collapse by different mental functions used in everyday life. Three mental functions are described, one of which is responsible for observation, and the others for conservation and treatment of information in mental representation. Whereas observation produces information with certainty, the subsequent processes result in information that remains uncertain potentiality. In order to encompass uncertainty, multiple possibilities are simultaneously considered in mental superposition, one of which should represent the unknown future outcome in observable reality. During verification by new observation, all suggested potentialities necessarily collapse to one real outcome. The collapse of superposition does not occur in observable physical reality, but in its mental representation. Some physical principles—such as superposition, infinity and nothingness before the Big Bang—are pure phenomena of mental representation, which will always remain unverifiable by observation. This argument proves that mental representation brought about by the observer context participates in the production of mental models for the best approximation of physical reality.

Effect of Yoga Exercise on Cognitive Ability and Motor Function Recovery in Stroke Patients

Abstract: Exercise therapy is widely used in the rehabilitation of stroke patients. Yoga exercise therapy is the typical one, but its specific effect and mechanism of action have not yet been clearly explained. In this context, 58 cases of stroke patients were randomly divided into experimental group and control group. Then, the effect of yoga exercise on the recovery of cognitive ability and motor function of stroke patients was explored by means of clinical controlled experiments. Through the monitoring and comparison of cerebral blood oxygen content, brain feedback-related negativity (FRN) and modified Barthel index (MBI) between the two groups of patients, it was found that yoga exercise therapy actually has a significant effect on improving the cognitive ability and motor function of stroke patients. Besides, from the point of view of the specific mechanism, yoga increases the patient’s nerve excitability by increasing blood oxygen content in the brain, while the increase in nerve excitability further enhances the patient’s ability to reflect, think, and control the body, so as to ultimately improve their cognitive ability and motor function.

Visualization of Information

Abstract: One of the surprising and mysterious parts of nature is the form of life. Unlike other physical systems, living organisms exhibit a very peculiar property, i.e., they self-organize, reproduce, etc. Indeed, life has yielded a special aspect of which appears to be the time-reversal process of non-living physical systems in nature. Following the discussion of Schrodinger’s negative entropic aspect of life, it is outlined that biological property may correspond to the classical projection from the semantics of DNA encryption, which is associated with the Dirac-type negative sea of consciousness. In particular, this analogy is similar to the dual nature of light where the photon outcomes in classical space may be considered a projection from the quantum negative sea of consciousness, or aether. Indeed, life, which exhibits the aspect of negative entropy as suggested by Schrodinger, may be considered as an image of consciousness.

Efficiency of Double Inversion Recovery (DIR) Sequence in the Evaluation of Supratentorial Cortical Lesions in Multiple Sclerosis

Abstract: The aim of this study is to investigate if the three–dimensional (3D) double inversion recovery (DIR) sequence is superior compared to the 3D fluid–attenuated inversion–recovery (FLAIR) sequence in detecting intracortical, mixed, juxtacortical (JX), and deep grey matter (GM) lesions in multiple sclerosis (MS) patients. The correlation between intracortical lesion load and disability status was also investigated. Magnetic resonance imaging examinations of 24 patients (9 males, 15 females; mean age 34.4±12.0 (16-69) were retrospectively evaluated from our database. Lesions were counted and classified according to anatomic regions as intracortical, mixed, JX, and deep GM on the 3D DIR and FLAIR sequences. The incidence of lesions on the two sequences were identified and compared. The relationship between the number of lesions and type of MS, patient age, gender, duration of the disease, disability, the mean number of attacks per year and Expanded Disability Status Scale (EDSS) score was also investigated. More lesions were detected by the DIR sequence compared to the FLAIR sequence in all regions except for thalamus (11/12). The lesion detection superiority of DIR was statistically significant for intracortical lesions (p<0.001) and GM lesions (intracortical +mixed) (p<0.001). Lesion load of the JX area in the DIR sequence decreased as the disease duration (r=-0.444; p=0.030) and age (r=-0.473; p=0.020) increased. JX lesion load in the DIR sequence decreased as the number of attacks increased (r=-0.602; p=0.002). More mixed lesion load on the DIR sequence were found in cerebral atrophy group than in no cerebral atrophy group (p=0.026). EDSS score increased as the disease duration and number of attacks increased (p=0.003, p<0.001). There was no correlation between lesion location and EDSS score. The DIR sequence is superior to the FLAIR sequence in the detection of intracortical and GM lesions. Also, the mixed lesion load on the DIR sequence is correlated with cerebral atrophy.

Career Planning Decision-making of College Students Based on Cognitive Science

Abstract: Under severe employment pressure and competition conditions, it is the first issue for college students to make career planning decisions suitable for their own development, which is of great significance for improving college students' career efficacy and career maturity. This paper studies the career planning decision-making of college students based on cognitive science theory. The results show that career decision-making should emphasize the relationship between human and information, and human and value, and realize the compatibility and accessibility of career desire through the cognition of personal and career matching. In the career planning decision-making stage, group counselling intervention can significantly improve the career maturity of college students, and has long-term effectiveness on improving career planning decision-making of college students. The analysis on cognitive science theory finds that the ultimate goal of career planning decision-making is to improve the ability of career decision-makers through scientific information processing ability.

Prediction Method for Energy Consumption of High-rise Buildings Based on Artificial Neural Network and Big Data Analysis

Abstract: In terms of the fact that the thermal load of high-rise buildings is affected by a series of influence factors, including outdoor meteorological environment, architectural characteristics, and building envelope, it is difficult to use the traditional mechanism to construct the prediction model because there are many difficult parameters and the reliability of the predicted result is low. Based on big data, the energy consumption of high-rise buildings is predicted by BP and RBF artificial neural network analysis methods because the artificial neural network does not rely on the model. The experimental result shows that the two models can well predict the energy consumption of high-rise buildings. What’s more, RBF artificial neural network is more stable than BP in prediction, so it is more suitable to predict the energy consumption of high-rise buildings.

Effects of Morchella esculenta Acidic Polysaccharide on Nerve Growth Factor of Diabetes Mellitus Rats

Abstract: This paper aims to disclose the hyperglycaemic activity of the polysaccharides extracted from Morchella esculenta (M. esculenta) mycelia. To this end, M. esculenta mycelia were cultured submerged fermentation, and the acidic polysaccharides were extracted and purified by anion exchange chromatography gel permeation chromatography. Then, a group of healthy rats was prepared, together with several groups of diabetes mellitus (DM) rats intervened with different doses of M. esculenta acidic polysaccharides. Next, several Morris water maze (MWM) tests were performed to reveal the regulation effect of these polysaccharides on the mRNA expression of the nerve growth factor (NGF) of the rats. The main results are as follows. The fasting blood glucose (FBG) and serum insulin (INS) of Group D (intervened by 600 μg∙mL-1 of polysaccharide) plunged to 8.12mmol/L and 31.67mU/L, respectively, compared to those of the control group (P<0.01), indicating that the polysaccharides can promote INS secretion. Meanwhile, the relative mRNA expression level of Group D grew by from the level of the control group (p<0.01). Thus, the acidic M. esculenta polysaccharide must have triggered the expression of NGF protein. The research findings lay a solid basis for the development of anti-hyperglycaemia food based on M. esculenta polysaccharides.