Nowadays, depression is the world’s major health concern and economic burden worldwide. However, due to the limitations of current methods for depression diagnosis, a pervasive and objective approach is essential. In the present study, a psychophysiological database, containing 213 subjects, was constructed. The electroencephalogram signals of all participants under resting state and sound stimulation were collected using a pervasive prefrontal-lobe three-electrode EEG system at Fp1, Fp2, and Fpz electrode sites. After denoising using the Finite Impulse Response filter combining the Kalman (...) derivation formula, Discrete Wavelet Transformation, and an Adaptive Predictor Filter, a total of 270 linear and nonlinear features were extracted. Then, the minimal-redundancy-maximal-relevance feature selection technique reduced the dimensionality of the feature space. Four classification methods distinguished the depressed participants from normal controls. The classifiers’ performances were evaluated using 10-fold cross-validation. The results showed thatK-Nearest Neighbor had the highest accuracy of 79.27%. The result also suggested that the absolute power of the theta wave might be a valid characteristic for discriminating depression. This study proves the feasibility of a pervasive three-electrode EEG acquisition system for depression diagnosis. (shrink)
BackgroundAging and type 2 diabetes mellitus are important risk factors for the development of cognitive deterioration and dementia. The objective of this research was to investigate the effects of an exercise intervention on cognitive function in older T2DM patients.MethodsEight literature databases were searched from inception to 20 January 2022. The researchers examined randomized controlled trials that evaluated the impact of exercise on the cognitive performance of older T2DM patients. The Cochrane risk-of-bias tool for RCTs was used to assess each study. (...) The quality of evidence was assessed using the GRADE approach. The mini-mental state examination, Modified MMSE, and Montreal cognitive assessment were used to evaluate the cognitive outcomes. We performed a subgroup analysis with stratification according to exercise intervention modality, duration, and cognitive impairment.ResultsFive trials were eligible, with a total of 738 T2DM patients. The combined findings revealed that exercise improved global cognitive function significantly. In the studies that were included, no relevant adverse events were reported.ConclusionExercise is beneficial in improving global cognitive function in older adults with T2DM. Studies with bigger sample sizes and higher quality are additionally expected to draw more definite conclusions.Systematic Review Registration[https://www.crd.york.ac.uk/PROSPERO/#recordDetails], identifier [CRD42022296049]. (shrink)
According to the conflict monitoring hypothesis, conflict monitoring and inhibitory control in cognitive control mainly cause activity in the anterior cingulate cortex and control-related prefrontal cortex in many cognitive tasks. However, the role of brain regions in the default mode network in cognitive control during category induction tasks is unclear. To test the role of the ACC, PFC, and subregions of the DMN elicited by cognitive control during category induction, a modified category induction task was performed using simultaneous fMRI scanning. (...) The results showed that the left middle frontal gyrus and bilateral dorsal ACC/medial frontal gyrus were sensitive to whether conflict information appears, but not to the level of conflict. In addition, the bilateral ventral ACC, especially the right vACC, a part of the DMN, showed significant deactivation with an increase in cognitive effort depending on working memory. These findings not only offer further evidence for the important role of the dorsolateral PFC and dorsal ACC in cognitive control during categorization but also support the functional distinction of the dorsal/ventral ACC in the category induction task. (shrink)
Green housing is a new type of building that advocates energy saving and environmental protection. How to stimulate buyers to buy green housing under the background of high cost is the key problem to guide green consumption. First of all, based on the existing literature, the comment of homebuyers was divided into comment quantity, comment quality, comment titer and evaluator credibility. The psychological distance mediation variable was introduced, and three dimensions of time distance, social distance, and space distance were selected (...) to construct the influence model of homebuyer comment on green housing purchase intention. Meanwhile, the concept model was built, and questionnaires were adopted for empirical analysis. On this basis, considering the long-term purchase behavior of buyers, the influence model of homebuyers' second comment on green housing purchase intention with the Hotelling model was established. The results show that comment quality, comment titer, and the credit rating of the evaluator have a positive effect on green housing purchase intention while comment quantity has no significant effect. Psychological distance plays a mediation role between comment quality, comment titer, the credit rating of the evaluator, and green housing purchase intention while having a mediation effect between comment quantity and green housing purchase intention. In the long-term purchase behavior of green housing, psychological distance plays a greater role than price. At last, some suggestions were proposed. (shrink)
This study utilizes hierarchical regression analysis to explore how environmental management systems influence financial performance through customer satisfaction and customer loyalty, and the moderating effects of switching cost. The originality of the present research is to unpack the “black box” through which a firm can profit from EMSs. The empirical results indicate that EMSs have positive and significant impacts on customer satisfaction, customer loyalty, and financial performance. In addition, switching cost negatively and significantly moderates the relationship between EMSs and customer (...) satisfaction, but does not significantly moderates the relationship between EMSs and customer loyalty. The results also demonstrate that customer satisfaction and customer loyalty partially mediate the relationship between EMSs and financial performance. Our findings highlight that customer satisfaction, customer loyalty, and switching cost play important roles for a firm to profit from EMSs. (shrink)
This study investigated whether ruminating on an intrusive thought before sleeping led to an increased likelihood of dreaming of threatening events. One hundred and forty-six participants were randomly assigned to a rumination condition and a control condition. Participants completed a dream diary upon waking. The result showed that presleep ruminating on an intrusive thought increased the frequency of both threatening dreams and negative emotions in dreams. In addition, dreams with threatening events were more emotional and negative than dreams without threatening (...) events. These results may support the threat simulation theory of dreaming. In addition, these results may give some insight into a mathematical model for the continuity hypothesis of dreaming. (shrink)
The coronavirus disease 2019 pandemic has been regarded as a public health emergency that caused a considerable degree of public panic during its early stage. Some irrational behaviors were also triggered as a result of such panic. Although there has been plenty of news coverage on public panic due to the outbreak, research on this phenomenon has been limited. Since panic is the main psychological reaction in the early stage of the pandemic, which largely determines the level of psychological adaptation, (...) time of psychological recovery, and the incidence of PTSD, there exists a demand to conduct investigation on it. From a public governance perspective, the government’s assessment of public panic may affect the efficiency and effectiveness of pandemic prevention and control. Therefore, it is of obvious practical significance to investigate public panic during the COVID-19 pandemic and analyze its influential factors. The self-compiled COVID-19 Social Mentality Questionnaire was used to collect data from a total of 16,616 participants online, and 13,511 valid responses were received. The results from the chi-square test showed that there were differences in gender, educational level, age, pandemic-related knowledge, self-efficacy, risk level, and objective social support. Furthermore, multiple linear regression analysis results showed that self-efficacy, gender, educational level, age, risk level, pandemic-related knowledge, and objective social support were significant predictors of public panic. Among the research variables, self-efficacy, gender, educational level, and age were negative predictors of panic while risk level, pandemic-related knowledge, and objective social support were positive predictors of panic. (shrink)
As the pace of modern life accelerates, social exclusion occurs more and more frequently in interpersonal interactions. The type of social exclusion can lead to different psychological needs of individuals, and, thus, affects the tendency of word-of-mouth recommendation. There are three experiments in this research. Experiment 1 explores the influence of social exclusion types on the willingness of WOM recommendation. The result shows that being rejected increases individuals' willingness to WOM recommendations while being ignored decreases individuals' willingness. Experiment 2 explores (...) the internal psychological mechanism of the influence of social exclusion types on WOM recommendation behavior and proves the mediating role of psychological needs. In experiment 3, the moderating effect of product attributes on the main effect is analyzed. This research is the first to explore the influence of social exclusion types on individuals' willingness to WOM recommendations, which enriches the research on social exclusion in the field of WOM recommendations. (shrink)
With the increasingly crowded shopping environment, social crowding has become an important factor that affects consumers’ psychology and behavior. However, the impact of social crowding on consumers’ preference for green products hasn’t been focused on. Therefore, the aim of this paper is to empirically investigate the influence of social crowding on consumers’ preference for green products. With four studies, the present research examines how social crowding influences consumers’ preferences and uncovers the underlying psychological mechanism. The research shows that consumers prefer (...) green products more under the condition of high social crowding than low, and safety needs mediate the impact of social crowding on green products preference. However, the impact of social crowding on the preference for products is only significant in green products. It also demonstrates the moderating effect of introversion-extraversion personality traits between social crowding and green products preference. For extraverted consumers, social crowding won’t affect their preference for green products, while for introverted consumers, social crowding is more likely to increase their preference for green products. This study contributes to marketing research by proposing and testing a new mechanism that underlies social crowding. (shrink)
This study explored and compared the perspectives of Taiwanese in-service and pre-service high school mathematics teachers regarding ideal teaching behaviours; the perspectives of a nationwide sample of students were taken as the baseline. Fourteen factors contributing to ideal teaching behaviours were identified through exploratory factor analyses. Nine factors, including idea explanation and speedy lecture, were rooted in traditional Chinese culture; five factors, including concrete representation and student activities, were influenced by Western cultures. Three teacher profiles were identified through k-means clustering (...) analysis. The perspectives of in-service teachers were dominated by a painless meaning-emphasised profile; these teachers emphasised meaningful learning for students and avoided the fast pace and demanding requirements that can cause distress in students, whereas pre-service teachers were dominated by an all-round profile, revealing their openness to all factors. Compared with... (shrink)
According to resource limitation, a more realistic pest management is that the impulsive control actions should be adjusted according to the densities of both pest and natural enemy in the field, which result in nonlinear impulsive control. Therefore, we have proposed a Beddington–DeAngelis interference predator-prey model concerning integrated pest management with both density-dependent pest and natural enemy population. We find that the pest-eradication periodic solution is globally stable if the impulsive period is less than the critical value by Floquet theorem. (...) The condition of permanent is established, and a stable positive periodic solution appears via a supercritical bifurcation by bifurcation theorem. Finally, in order to investigate the effects of those nonlinear control strategies on the successful pest control, the bifurcation diagrams showed that the model exists with very complex dynamics. Consequently, the resource limitation may result in pest outbreak in complex ways, which means that the pest control strategies should be carefully designed. (shrink)
With significant development of sensors and Internet of things, researchers nowadays can easily know what happens in physical space by acquiring time-varying values of various factors. Essentially, growing data category and size greatly contribute to solve problems happened in physical space. In this paper, we aim to solve a complex problem that affects both cities and villages, i.e., flood. To reduce impacts induced by floods, hydrological factors acquired from physical space and data-driven models in cyber space have been adopted to (...) accurately forecast floods. Considering the significance of modeling attention capability among hydrology factors, we believe extraction of discriminative hydrology factors not only reflect natural rules in physical space, but also optimally model iterations of factors to forecast run-off values in cyber space. Therefore, we propose a novel data-driven model named as STA-LSTM by integrating Long Short-Term Memory structure and spatiotemporal attention module, which is capable of forecasting floods for small- and medium-sized rivers. The proposed spatiotemporal attention module firstly explores spatial relationship between input hydrological factors from different locations and run-off outputs, which assigns time-varying weights to various factors. Afterwards, the proposed attention module allocates temporal-dependent weights to hidden output of each LSTM cell, which describes significance of state output for final forecasting results. Taking Lech and Changhua river basins as cases of physical space, several groups of comparative experiments show that STA-LSTM is capable to optimize complexity of mathematically modeling floods in cyber space. (shrink)
This study focuses on the static output feedback control of nonlinear Markov jump singularly perturbed systems within the framework of Takagi–Sugeno fuzzy approximation. From a practical point of view, the phenomenon of asynchronous switching between the plant and the controller is considered and characterized by a finite piecewise-homogenous Markov process. Particularly, for facilitating the controller synthesis, the closed-loop system is transformed into a fuzzy Markov jump singularly perturbed descriptor system by adopting descriptor representation. In order to fully accommodate the system (...) features, an appropriate stochastic Lyapunov function is constructed. Afterwards, by combining Finsler’s lemma, the mean square exponential admissibility of the system is analyzed. The conditions ensuring the existence of the predesigned controller are given and further solved by designing a brief search algorithm. Finally, a typical circuit system is used to demonstrate the application potential of the developed control technology and the effectiveness of the control strategy. (shrink)
This study aimed to develop and test the reliability and validity of a multi-item nurses’ presenteeism behaviour questionnaire. Study 1 administered the Nurse Presenteeism Questionnaire to 250 Chinese nurses. Study 2, surveyed 650 nurses with the NPQ, the Sickness Presenteeism Questionnaire, the Stanford Presenteeism Scale, the General Health Questionnaire, and the Emotional Exhaustion Scale using convenience sampling. After item analysis, the subjects were randomly divided into two groups to verify the questionnaire structure. Study 1 revealed the nurses’ core symptoms when (...) they go to work with illness, and the NPQ with 11 items was developed. Study 2’s item analysis revealed that 11 NPQ items had good discrimination and high homogeneity. Besides, the scale had good reliability and external criterion validity. Thus, the NPQ can be used to measure presenteeism behaviour in nursing. (shrink)
This study adopts an intrapersonal perspective to explore how and when employees shift roles from help giver to help seeker by investigating the relationship between their help-giving and following help-seeking behavior. Based on self-regulation theory, we hypothesize two contradictory psychological processes via which employees determine whether to seek help after giving help. Importantly, we differentiate autonomous help-seeking from dependent help-seeking and propose stronger effects of help-giving on dependent help-seeking. Further, we identify leader respect as a moderator to solve the opposite (...) effects of employees’ help-giving on their subsequent help-seeking indicated by the two contradictory mechanisms. Results of two field studies consistently showed that the negative relationship between help-giving and dependent help-seeking was serially mediated by personal reputation and reputation maintenance concerns. Results regarding autonomous help-seeking were inconsistent and help-giving only positively affected autonomous help-seeking via perceived increase of moral credits and help-seeking justification in Study 2. Leader respect weakened the positive but strengthened the negative relationship. We discuss theoretical implications for helping literature, self-regulation theory, and moral behavior research. (shrink)
In this study, we tested a possible mechanism of the association between math anxiety and math achievement: the mediating role of math-specific grit. In Study 1, a sample of 10th grade students completed a battery of personality and attitude questionnaires, and math achievement was indexed by curriculum-based examination scores. Mediation analyses indicated that math-specific grit, but not domain-general grit, mediated the relationship between math anxiety and math achievement. In Study 2, we replicated and extended the above findings with another sample (...) of 11th grade students. Mediation analyses indicated that math-specific grit and math-specific procrastination played sequential mediating roles in the relationship between math anxiety and math achievement. That is, individuals with higher math anxiety were less gritty in math learning, possibly further leading them to be more procrastinated in performing math work, which may finally result in worse math achievement. In summary, the current study provides the first evidence that math-specific grit may mediate the relationship between math anxiety and math achievement. Furthermore, it also demonstrated the value of math-specific grit over domain-general grit in predicting math success, which invites a broader investigation on subject-specific grit. (shrink)
A reservoir was dominated by inclined heterolithic stratification formed in large point bars of the McMurray Formation. We have used high-resolution seismic data and logging data to identify the internal architectural elements of the reservoir. From the core data, we defined four lithofacies and recognized the architectural element boundary. Then, we used stratum dip data across wells, combined with seismic reflectivity, isopach, and amplitude attributes, to understand the lateral continuity of the boundaries. Later, we established the sedimentary model and found (...) the differences between tidal-influenced meandering fluvial channels and conventional meandering fluvial channels. Research showed that tidal bedding was especially well-developed, and breccia deposition and muddy IHS were also frequent. The development of the lateral accretion packages was more frequent than that in the conventional meandering fluvial channels. The characteristics of the interbedded layers in sandy IHS were very thin, mainly approximately 20 to 40 cm. The dip of the lateral accretion packages was smaller and distributed from 4° to 8°. The studies were expected to have a major impact on the understanding of reservoir formation, distribution, and heterogeneity for improved hydrocarbon recovery purpose in the area. (shrink)
Mismatch negativity of event-related potentials is a biomarker reflecting the preattentional change detection under non-attentional conditions. This study was performed to explore whether high self-related information could elicit MMN in the visual channel, indicating the automatic processing of self-related information at the preattentional stage. Thirty-five participants were recruited and asked to list 25 city names including the birthplace. According to the difference of relevance reported from the participants, we divided names of the different cities into high, medium, and low self-related (...) information. Visual MMN was elicited by high self-related information but not by medium self-related information, with an occipital–temporal scalp distribution, indicating that, under non-attentional condition, high self-related information can be effectively processed automatically in the preattentional stage compared with low self-related information. These data provided new electrophysiological evidence for self-related information processing. (shrink)
In natural environments, organic-clay interactions are strong and cause organo-clay composites to be one of the predominant forms for OM occurrence, and their interactions greatly influence the hydrocarbon generation of OM within source rocks. However, despite occurring in nature, dominating the OM occurrence, and having unique HC generation ways, organo-clay composites have rarely been investigated as stand-alone petroleum precursors. To improve this understanding, we have compared the Rock-Eval pyrolysis parameters derived from more than 100 source rocks and their corresponding <2 (...) μm clay-sized fractions. The results show that all of the Rock-Eval pyrolysis parameters in bulk rocks are closely positively correlated with those in their clay-sized fractions, but in clay-sized fractions the quality of OM for HC generation is poorer, in that the pyrolysable organic carbon levels and hydrogen index values are lower, whereas the residual organic carbon levels are higher than those in bulk rocks. Being integrated with the effects of organic-clay interactions on OM occurrence and HC generation, our results suggest that organo-clay composites are stand-alone petroleum precursors for HC generation occurring in source rocks, even if the source rocks exist in great varieties in their attributes. Our source material for HC generation comprehensively integrates the original OM occurrence and HC generation behavior in natural environments, which differs from kerogen and is much closer to the actual source material of HC generation in source rocks, and it calls for further focus on organic-mineral interactions in studies of petroleum systems. (shrink)
Music education is one of human kind most universal forms of expression and communication, and it can be found in the daily lives of people of all ages and cultures all over the world. As university life is a time when students are exposed to a great deal of stress, it can have a negative impact on their mental health. Therefore, it is critical to intervene at this stage in their life so that they are prepared to deal with the (...) pressures they will face in the future. The aim of this study was to see how music education affects university students’ mental health, with emotional intelligence functioning as a moderator. The participants in this research were graduate students pursuing degrees in music education. Non probability convenience sampling technique was used to collect and evaluate the data from 265 students studying in different public and private Chinese universities. The data was gathered at a time, and therefore, the study is cross-sectional. The data was collected from January 2022 till the end of March 2022. Many universities have been closed because to COVID-19, therefore data was also gathered online through emails. The data was analyzed quantitatively using the partial least squares –structural equation modeling technique. The findings backed up the hypotheses. The results revealed that there is a significant effect of music education on student’s mental health. Also, emotional intelligence as a moderator significantly and positively moderates the relationship between music education and students’ mental health. Music has numerous physiological aspects, and listening to it on a daily basis may be beneficial to your general health and well-being. Furthermore, musicians and music students with a high level of emotional intelligence have a better chance of not just performing well in school, college and university or in the music industry, but also of maintaining mental health and improving it. (shrink)
Tradition wireless sensor networks transmit data by single or multiple hops. However, some sensor nodes close to a static base station forward data more frequently than others, which results in the problem of energy holes and makes networks fragile. One promising solution is to use a mobile node as a mobile sink, which is especially useful in energy-constrained networks. In these applications, the tour planning of MS is a key to guarantee the network performance. In this paper, a novel strategy (...) is proposed to reduce the latency of mobile data gathering in a WSN while the routing strategies and tour planning of MS are jointly optimized. First, the issue of network coverage is discussed before the appropriate number of clusters being calculated. A dynamic clustering scheme is then developed where a virtual cluster center is defined as the MS sojourn for data collection. Afterwards, a tour planning of MS based on prediction is proposed subject to minimizing the traveling distance to collect data. The proposed method is simulated in a MATLAB platform to show the overall performance of the developed system. Furthermore, the physical tests on a test rig are also carried out where a small WSN based on an unmanned aerial vehicle is developed in our laboratory. The test results validate the feasibility and effectiveness of the method proposed. (shrink)
Height measurement for moving pedestrians is quite significant in many scenarios, such as pedestrian positioning, criminal suspect tracking, and virtual reality. Although some existing height measurement methods can detect the height of the static people, it is hard to measure height accurately for moving pedestrians. Considering the height fluctuations in dynamic situation, this paper proposes a real-time height measurement based on the Time-of-Flight camera. Depth images in a continuous sequence are addressed to obtain the real-time height of the pedestrian with (...) moving. Firstly, a normalization equation is presented to convert the depth image into the grey image for a lower time cost and better performance. Secondly, a difference-particle swarm optimization algorithm is proposed to remove the complex background and reduce the noises. Thirdly, a segmentation algorithm based on the maximally stable extremal regions is introduced to extract the pedestrian head region. Then, a novel multilayer iterative average algorithm is developed for obtaining the height of dynamic pedestrians. Finally, Kalman filtering is used to improve the measurement accuracy by combining the current measurement and the height at the last moment. In addition, the VICON system is adopted as the ground truth to verify the proposed method, and the result shows that our method can accurately measure the real-time height of moving pedestrians. (shrink)
Tight sands have pore systems with complex structures and widely distributed pore sizes. We have studied the characteristics of these pore systems to better understand their important role in the accumulation and migration mechanisms of oil and gas reservoirs, which may enhance our ability to evaluate reservoir quality and predict reservoir production. To this end, we carried out thin-section analysis, scanning electron microscopy, pressure-controlled porosimetry, and rate-controlled porosimetry to describe the pore systems of a typical tight-sand reservoir in East Asia. (...) We improved a differential-distribution-based splicing method to reveal the full-scale pore systems using PCP and RCP. We found that the typical pore radius distribution in our target reservoir exhibits two peaks: at radius [Formula: see text] and at radius [Formula: see text]. Based on pore shapes and connections, intergranular pores are network structures and clay-host pores are tree-like structures. Intragranular pores, in contrast, can be different structures under different conditions. If wide throats are present, intragranular pores function as typical tree-like pores; if throats are narrow, they serve as the pore parts of a network-pore system. Network pores are the primary contributors to porosity and permeability, whereas tree-like pores mainly contribute to porosity. In some high-clay sands, however, the tree-like pores may also contribute to permeability. Based on their fractal characteristics, we divided the pore systems of tight sands into three types: a network-structure-controlled intergranular pore system, a tree-like-structure-controlled clay-host pore system, and a network-structure-controlled intergranular-intragranular pore system. (shrink)
In the era of big data, data-driven methods mainly based on deep learning have been widely used in the field of intelligent fault diagnosis. Traditional neural networks tend to be more subjective when classifying fault time-frequency graphs, such as pooling layer, and ignore the location relationship of features. The newly proposed neural network named capsules network takes into account the size and location of the image. Inspired by this, capsules network combined with the Xception module is applied in intelligent fault (...) diagnosis, so as to improve the classification accuracy of intelligent fault diagnosis. Firstly, the fault time-frequency graphs are obtained by wavelet time-frequency analysis. Then the time-frequency graphs data which are adjusted the pixel size are input into XCN for training. In order to accelerate the learning rate, the parameters which have bigger change are punished by cost function in the process of training. After the operation of dynamic routing, the length of the capsule is used to classify the types of faults and get the classification of loss. Then the longest capsule is used to reconstruct fault time-frequency graphs which are used to measure the reconstruction of loss. In order to determine the convergence condition, the three losses are combined through the weight coefficient. Finally, the proposed model and the traditional methods are, respectively, trained and tested under laboratory conditions and actual wind turbine gearbox conditions to verify the classification ability and reliable ability. (shrink)
Understanding pore growth is of great significance to investigating reservoir performance in shale-gas systems. However, different from the marine shale reservoir, the lacustrine shale reservoir is commonly rich in clay minerals, resulting in a complicated and poorly understood pore system. We have investigated the impact of coexisting clay mineral and organic matter on pore growth in the Lower Jurassic Da’anzhai Shale in the Northeast Sichuan Basin, West China, through performing total organic carbon analysis, X-ray diffraction, field-emission scanning electron microscopy, focused (...) ion beam-scanning electron microscopy, [Formula: see text] and [Formula: see text] adsorption experiment, and high-pressure mercury intrusion porosimetry. Our results indicate that the Da’anzhai Shale is dominated by clay-mineral-hosted pores, which are commonly filled or partly filled by pyrobitumen. Controlled by organic maceral, organic pores are poorly and heterogeneously developed in pyrobitumen, and minor or even no organic pores grow in vitrinite. Mesopore and macropore are popular in the Da’anzhai Shale reservoir with complex shapes, e.g., slit- or plate-like shapes combined with “ink-bottle” shapes, confirming a pore system dominated by clay-mineral-hosted pores. The weak positive correlation between the clay mineral content and the meso/macropore volume confirms that the clay mineral is a positive contributor to the storage space, and the weak negative correlation between the TOC and the mesopore volume suggests that infilling of pyrobitumen decreases the pore volume significantly. Similar correlations occur between specific surface area and clay mineral/TOC. FIB-SEM observation confirms that the pore system, e.g., the pore size, pore shape, and pore volume, is controlled by the coexisting clay mineral and pyrobitumen filling in a later stage. The calculated plane porosity of the initial inorganic pore and the unfilled inorganic pore in the Da’anzhai Shale is in the range of 3.66%–10.95% and 0.79%–1.46%, respectively, suggesting that 76.66% of inorganic pores is inactive due to pyrobitumen filling. All of this evidence suggests that pore growth in the Da’anzhai Shale is positively contributed by clay minerals, but it is negatively contributed by pyrobitumen filling. Further discussion suggests that pyrobitumen infilling between clay minerals in the Da’anzhai lacustrine shale can decrease the original pore volume significantly, which work together to govern the pore system in shale reservoirs. (shrink)
Efficient knowledge sharing is an important support for the continuous innovation and sustainable development of scientific research teams. However, in realistic management situations, the knowledge sharing of scientific research teams always appears to be unsustainable, and the reasons for this are the subject of considerable debate. In this study, an attempt was made to explore the interactive mechanism of knowledge hiding behaviors in scientific research teams between individual and collective knowledge hiding behaviors and its impact on knowledge sharing by adopting (...) grounded theory to comprehensively understand this situation. The results show that knowledge hiding behavior in the scientific research team is a two-phase interactive process and is capable of affecting sustainable knowledge sharing by reducing the supply of knowledge, creating a poor knowledge sharing atmosphere, and forming an interpersonal distrust relationship. This research may provide a strong basis for a deeper understanding of the interaction mechanism of knowledge hiding behavior and its impact on knowledge sharing. (shrink)
Point-of-interest recommendations are a popular form of personalized service in which users share their POI location and related content with their contacts in location-based social networks. The similarity and relatedness between users of the same POI type are frequently used for trajectory retrieval, but most of the existing works rely on the explicit characteristics from all users’ check-in records without considering individual activities. We propose a POI recommendation method that attempts to optimally recommend POI types to serve multiple users. The (...) proposed method aims to predict destination POIs of a user and search for similar users of the same regions of interest, thus optimizing the user acceptance rate for each recommendation. The proposed method also employs the variable-order Markov model to determine the distribution of a user’s POIs based on his or her travel histories in LBSNs. To further enhance the user’s experience, we also apply linear discriminant analysis to cluster the topics related to “Travel” and connect to users with social links or similar interests. The probability of POIs based on users’ historical trip data and interests in the same topics can be calculated. The system then provides a list of the recommended destination POIs ranked by their probabilities. We demonstrate that our work outperforms collaborative-filtering-based and other methods using two real-world datasets from New York City. Experimental results show that the proposed method is better than other models in terms of both accuracy and recall. The proposed POI recommendation algorithms can be deployed in certain online transportation systems and can serve over 100,000 users. (shrink)
This book provides a reexamination of the debates between Hu Feng, Lu Ling, and other Chinese left-wing theorists from a cultural-political perspective. The author argues that individualism should be understood within changing historical contexts and that subjectivity should be treated as class-based and derived from collective community.
Cognitive diversity is an important concept stemming from western management research in the 1990s. With the rapid development of science and technology, there is a growing interest in the composition of an academic research team, such as team diversity. However, there is no tool available for measuring team cognitive diversity for academic research teams. Based on Van der Vegt’s theoretical model of TCD, an Academic Research Team Cognitive Diversity Scale is developed and validated for an academic research team in our (...) research with two studies. In Study One, in-depth interviews and panel discussions were conducted to generate a preliminary questionnaire. In Study Two, the questionnaire was administered among academic research teams. Exploratory factor analysis revealed four factors regarding cognitive diversity: the way of thinking, knowledge and skills, the view of the world, and beliefs about what is right and wrong. The factor structure was further validated by confirmatory factor analysis. Moreover, correlation and regression analyses showed that academic research TCD was positively related to team creativity and performance. To sum up, our newly developed 15-item ATCDS is sufficiently reliable and valid to be used for understanding cognitive diversity among academic research teams. (shrink)
Chaos theory has been proved to be of great significance in a series of critical applications although, until now, its applications in analyzing soil respiration have not been addressed. This study aims to introduce a chaotic component in the control system of soil respiration and explain control complexity of this nonlinear chaotic system. This also presents a theoretical framework for better understanding chaotic components of soil respiration in arid land. A concept model of processes and mechanisms associated with subterranean CO2 (...) evolution are developed, and dynamics of the chaotic system is characterized as an extended Riccati equation. Controls of soil respiration and kinetics of the chaotic system are interpreted and as a first attempt, control complexity of this nonlinear chaotic system is tackled by introducing a period-regulator in partitioning components of soil respiration. (shrink)
Traffic congestion is a common problem in many countries, especially in big cities. At present, China’s urban road traffic accidents occur frequently, the occurrence frequency is high, the accident causes traffic congestion, and accidents cause traffic congestion and vice versa. The occurrence of traffic accidents usually leads to the reduction of road traffic capacity and the formation of traffic bottlenecks, causing the traffic congestion. In this paper, the formation and propagation of traffic congestion are simulated by using the improved medium (...) traffic model, and the control strategy of congestion dissipation is studied. From the point of view of quantitative traffic congestion, the paper provides the fact that the simulation platform of urban traffic integration is constructed, and a feasible data analysis, learning, and parameter calibration method based on RBF neural network is proposed, which is used to determine the corresponding decision support system. The simulation results prove that the control strategy proposed in this paper is effective and feasible. According to the temporal and spatial evolution of the paper, we can see that the network has been improved on the whole. (shrink)