Ecological innovation is an inevitable trend for firms to enhance competitiveness and sustainably operate in the context of green economy. The previous literature has rarely discussed the influence of ambidextrous learning on the eco-innovation performance of startups and ignored the moderating effect of top management’s environmental awareness from the perspective of microscopic psychology. We have conducted a questionnaire survey on 212 firms established within 4 years in the Pearl River Delta of China, using the structure mode and the PROCESS by (...) Hayes (2013) to analyze the influence of ambidextrous learning, such as exploratory learning and exploitative learning, by startups on eco-innovation performance and verify the moderating effect of top management’s environmental awareness. The results show that: exploratory learning and exploitative learning have a positive and significant influence on eco-innovation performance, indicating that the organizational learning of startups is conducive to improving eco-innovation performance; under the moderating effect of top management’s environmental awareness, the influence of exploratory learning and exploitative learning on eco-innovation performance may differ. The results also show that in the process of organizing ambidextrous learning, startups should help raise the environmental awareness of top management to improve the eco-innovation performance, thus providing guidance for startups to carry out eco-innovation activities and for local governments to make decisions on green economy. (shrink)

Entrepreneurship may be taught, and entrepreneurship education is flourishing at colleges and universities. However, previous documents show that entrepreneurship education is inconsistent with the research conclusions of entrepreneurial intention, which is a lack of discussion on the mediating effect of government subsidies from external resources. Based on the cognitive behavior theory, a mediating effect of entrepreneurship education on entrepreneurial strategy and entrepreneurial intention is built. By collecting the data of 334 questionnaires of college students in Pearl River Delta in China, (...) a structural equation is used for empirical analysis. The result indicates that entrepreneurship education does not have a significant influence on entrepreneurial intention; exploration innovation and exploitation innovation have a positive influence on entrepreneurial intention, and exploration innovation and exploitation innovation have a mediating effect on entrepreneurship education and entrepreneurial intention; government subsidies have a positive regulating effect on exploration innovation, exploitation innovation, and entrepreneurial intention. In this article, the application of the cognitive behavior theory in the field of entrepreneurship research is expanded to provide the theoretical basis for building the entrepreneurship education ecosystem, which is conductive to innovation and entrepreneurship to promote regional economic development. (shrink)

Pharmaceutical supply chains are often highly complex with conflicting objectives of social welfare and profit maximization. Furthermore, there are various stakeholders including pharmaceutical manufacturer, distributors, retailers, patients, and the government. In this paper, we consider a two-stage supply chain consisting of one pharmaceutical manufacturer and a pharmacy with online and offline channels. We focus on four price cap models: no price cap regulation, pharmaceutical manufacturer’s price cap regulation, pharmacy price cap regulation, and linkage price cap regulation. We apply game theory, (...) investigate how the price cap regulations affect the firms’ pricing, and evaluate the economic performance and social welfare of the dual-channel pharmaceutical supply chain. Our findings show that first, like the single-channel pharmaceutical supply chain, the profit of the regulated firm always decreases and the profit of the unregulated firm always increases when they are under one-sided price cap regulations. Second, the impacts of the linkage price cap regulation on the supply chain are more complicated depending on the linkage coefficient and market share. Overall, our findings can provide theoretical and practical insights to help the government devise price cap regulations for complex modern pharmaceutical supply chains. (shrink)

本书阐明自然辩证法这门学科的形成过程,概要地阐述它的基本原理及其一百多年的发展历史。.

Marxist dialectic in the era of scientific and technological revolution.

This study conducted a cross-sectional investigation of facial appearance dissatisfaction between patients before undergoing orthognathic surgery and a non-surgical sample to evaluate the potential influencing factors of facial appearance dissatisfaction. A sample of 354 participants completed a set of questionnaires concerning facial appearance dissatisfaction, interpersonal pressure, media pressure, and fear of negative appearance evaluation (112 patients, 242 controls). The patients reported higher facial appearance dissatisfaction, more media pressure, more interpersonal pressure, and a greater fear of negative appearance evaluation among others (...) than the control group. Moreover, regression analyses identified interpersonal pressure and fear of negative appearance evaluation as the main influencing factors on facial appearance dissatisfaction whether in the orthognathic patients or in the control groups. The associations between the perceptions of interpersonal pressure, fear of negative appearance evaluation, and facial appearance dissatisfaction support the possible utility of strengthening social experiences and psychological intervention in preventing and treating these appearance-concerns, especially for the orthognathic patients. (shrink)

Computer technology and related Internet of things technology have penetrated into people’s daily life and industrial production; even in competitive sports training and competition, the Internet of things technology has also been a large number of applications. Traditional intelligent wearable devices are mainly used to calculate the steps of athletes or sports enthusiasts, corresponding physical data, and corresponding body indicators. The energy consumption calculated by these indexes is rough and the corresponding error is large. Based on this, this paper will (...) design a wearable device which can accurately calculate and monitor sports energy consumption based on relevant sensors and Internet of things technology. The corresponding core algorithm is the step counting algorithm, which can accurately calculate the relationship between human motion and the corresponding energy consumption and feed back to the intelligent device. In the experiment, the wearable device designed in this paper is compared with the traditional intelligent device. The experiment shows that the wearable device proposed in this paper is more accurate in energy consumption estimation than the traditional device, and its corresponding energy consumption is relatively small. (shrink)

Cell membranes experience frequent stretching and poking: from cytoskeletal elements, from osmotic imbalances, from fusion and budding of vesicles, and from forces from the outside. Are the ensuing changes in membrane tension localized near the site of perturbation, or do these changes propagate rapidly through the membrane to distant parts of the cell, perhaps as a mechanical mechanism of long‐range signaling? Literature statements on the timescale for membrane tension to equilibrate across a cell vary by a factor of ≈106. This (...) study reviews and discusses how apparently contradictory findings on tension propagation in cells can be evaluated in the context of 2D hydrodynamics and poroelasticity. Localization of tension in the cell membrane is likely critical in governing how membrane forces gate ion channels, set the subcellular distribution of vesicle fusion, and regulate the dynamics of cytoskeletal growth. Furthermore, in this study, it is proposed that cells can actively regulate the degree to which membrane tension propagates by modulating the density and arrangement of immobile transmembrane proteins. Also see the video abstract here https://youtu.be/T6K7AIAqqBs. (shrink)

This study is to explore the gesture recognition and behavior tracking in swimming motion images under computer machine vision and to expand the application of moving target detection and tracking algorithms based on computer machine vision in this field. The objectives are realized by moving target detection and tracking, Gaussian mixture model, optimized correlation filtering algorithm, and Camshift tracking algorithm. Firstly, the Gaussian algorithm is introduced into target tracking and detection to reduce the filtering loss and make the acquired motion (...) posture more accurate. Secondly, an improved kernel-related filter tracking algorithm is proposed by training multiple filters, which can clearly and accurately obtain the motion trajectory of the monitored target object. Finally, it is proposed to combine the Kalman algorithm with the Camshift algorithm for optimization, which can complete the tracking and recognition of moving targets. The experimental results show that the target tracking and detection method can obtain the movement form of the template object relatively completely, and the kernel-related filter tracking algorithm can also obtain the movement speed of the target object finely. In addition, the accuracy of Camshift tracking algorithm can reach 86.02%. Results of this study can provide reliable data support and reference for expanding the application of moving target detection and tracking methods. (shrink)

Extensive research has been carried out on the “Belt and Road” initiative, most of it focusing on geographical economy and international trade. However, there is a lack of research on the carbon emissions efficiency of the countries along the “Belt and Road,” especially regarding the impact of freight trade. To address this research gap, this paper first employs a metafrontier nonradial directional distance function to measure the carbon emission efficiency of 32 countries along the “Belt and Road” from 1990 to (...) 2014. It then examines the role of freight trade. Our main research findings are as follows. Firstly, the carbon emission efficiency of the countries along the “Belt and Road” is generally low. Among them, Russia and Central Asia are mainly due to the large between-group gap in carbon emission efficiency, while Southeast Asia, Western Asia and North Africa, East Asia, South Asia, and Central and Eastern Europe are mainly due to the large within-group gap. Secondly, freight trade promotes carbon emission efficiency, but it will aggravate the gap between the contemporaneous technology and the group technology. Freight trade mainly promotes the contemporaneous carbon emission efficiency and group-frontier carbon emission efficiency of low fossil energy dependent countries, and the metafrontier carbon emission efficiency of high fossil energy dependent countries. Thirdly, foreign direct investment has a significant negative effect on a host country’s ITCEI and GTCEI, and it will decrease the gap between the group technology and the metafrontier technology. However, freight trade can effectively prevent the entry of FDI, thereby indirectly improving carbon emission efficiency and reducing carbon emission gap. (shrink)

BackgroundDepression and alcohol dependence are among the most prevalent psychiatric disorders that commonly co-occur. Therefore, gaining a better grasp of factors related to this comorbidity is particularly interesting for clinicians. Past research has highlighted the significant role that time perspective and family history of alcohol dependence play in the occurrence of depression and AD. However, much remains unexplored in the understanding of the association between them. This study explored how temporal profile and other sociodemographic characteristics of patients diagnosed with AD (...) impact the severity of depression and AD in them.MethodsThis study was multi-centered, including 381 patients. Cross-sectional information was collected from both inpatient and outpatient psychiatric clinics in China. Data were acquired using validated self-report scales, including Michigan Alcoholism Screening Test, Zung Self-Rating Depression Scale, and Zimbardo Time Perspective Inventory-Chinese version. Multiple linear regression analyzes were conducted to control social demographic variables and construct prediction models to inspect the influence factors of variables. Moderation models were constructed to inspect further interplay between variables using hierarchical regression and PROCESS Macro.ResultsResults showed that of all the patients in Chinese psychiatry clinics diagnosed with AD according to the International Classification of Diseases-10, 59.9% met the criteria of depression according to the questionnaire, and time perspective was correlated with the severity of depression. Furthermore, using regression analysis, we found that time perspective and depression could predict AD severity. The moderating role of a past negative time perspective and FH was confirmed between depression and AD. We found that, in our study, only in patients with FH and relatively moderate to high scores of past negative time perspective could the severity of depression predict the severity of AD. Therefore, during the treatment and care of patients with AD, their depression level, time perspective score, and FH should be considered. (shrink)

Electroencephalogram has been widely utilized in emotion recognition. Psychologists have found that emotions can be divided into conscious emotion and unconscious emotion. In this article, we explore to classify subliminal emotions with EEG signals elicited by subliminal face stimulation, that is to select appropriate features to classify subliminal emotions. First, multi-scale sample entropy, wavelet packet energy, and wavelet packet entropy of EEG signals are extracted. Then, these features are fed into the decision tree and improved random forest, respectively. The classification (...) accuracy with Ei and WpEn is higher than MSpEn, which shows that Ei and WpEn can be used as effective features to classify subliminal emotions. We compared the classification results of different features combined with the decision tree algorithm and the improved random forest algorithm. The experimental results indicate that the improved random forest algorithm attains the best classification accuracy for subliminal emotions. Finally, subliminal emotions and physiological proof of subliminal affective priming effect are discussed. (shrink)

PurposeThis study aims to examine the mediating role recovery plays in the relationship between resilience and posttraumatic growth among breast cancer patients.MethodsA cross-sectional study design was implemented between January 02, 2021 and April 29, 2021. A total of 789 breast cancer patients from eight hospitals in Liaoning province were selected for participation in this study. These participants completed questionnaires, which included the Post-Traumatic Growth Inventory, EGO Resilience Scale and the Questionnaire about the Process of Recovery. The associated factors of PTG (...) were analyzed using hierarchical multiple regression. The proposed relationships among resilience, recovery, and PTG were checked by structural equation modeling analyses.ResultsThe average PTG score of breast cancer patients was 53.00 ± 28.30. PTG was positively correlated with both recovery and PTG.ConclusionBreast cancer patients were found to exhibit a moderate degree of PTG. Resilience was positively associated with PTG and recovery mediated the positive effect of resilience on PTG. Resilience might serve as a crucial protective factor that could explain positive growth in life-threatening illnesses through the mediating path of recovery. (shrink)

Physical activity is critical for maintaining cognitive and brain health. Previous studies have indicated that the effect of physical activity on cognitive and brain function varies between individuals. The present study aimed to examine whether mind wandering modulated the relations between physical activity and resting-state hippocampal functional connectivity. A total of 99 healthy adults participated in neuroimaging data collection as well as reported their physical activity in the past week and their propensity to mind wandering during typical activities. The results (...) indicated that mind wandering was negatively related to the resting-state functional connectivity between hippocampus and right inferior occipital gyrus. Additionally, for participants with higher level of mind wandering, physical activity was negatively related to hippocampal connectivity at left precuneus and right precentral gyrus. In contrast, such relations were positive at right medial frontal gyrus and bilateral precentral gyrus for participants with lower level of mind wandering. Altogether, these findings indicated that the relations between physical activity and hippocampal functional connectivity vary as a function of mind wandering level, suggesting that individual differences are important to consider when we aim to maintain or improve cognitive and brain health through increasing physical activity. (shrink)

In a sample of 522 police officers and staff in an English police force, we investigated the role of authoritarian leadership in reducing the levels of employee ethical voice. Drawing upon uncertainty management theory, we found that authoritarian leadership was negatively related to employee ethical voice through increased levels of felt uncertainty, when the effects of a motivational-based mechanism suggested by previous studies were controlled. In addition, we found that the negative relationship between authoritarian leadership and employee ethical voice via (...) felt uncertainty is mitigated by higher levels of benevolent leadership. That is, when authoritarian leaders simultaneously exhibit benevolence, they are less likely to cause feelings of uncertainty in their followers who are then more likely to speak up about unethical issues. We discuss theoretical and practical implications of the findings. (shrink)

As the essence of livestream e-commerce is social commerce, building a livestream brand community and attracting brand followers are the key aspects to achieving sustained revenue. For many companies, inviting celebrities has become a shortcut to attract new followers. Considering the unsustainability and high cost of the celebrity host mode, some companies switched to using their own branded broadcasters to attract followers. However, as branded broadcasters lack a fan base, choosing the suitable broadcaster type has become a challenge in livestream (...) e-commerce. The motivation of consumers to follow brand livestream accounts is mainly to obtain potential value by embedding them in social networks. Therefore, based on motive theory, this research explores how different broadcaster types affect consumer’s intention to follow a livestream brand community. Results from the analysis of secondary data from livestream platforms and two laboratory experiments reveal that celebrities contribute more to consumer’s intention to follow than branded broadcasters, and utilitarian products can strengthen the effect of branded broadcasters on attracting potential followers. Moreover, branded broadcasters can promote consumer’s intention to follow a livestream brand community by satisfying consumer’s need for informational value during utilitarian product evaluation. This research analyzes the differential effects of different types of broadcasters on livestream brand community building. The findings can deepen the understanding of the consumer’s behavior of following brand livestream communities and provide companies with suggestions on broadcaster selection in livestream e-commerce. (shrink)

Recurrent neural network has been widely applied to many sequential tagging tasks such as natural language process and time series analysis, and it has been proved that RNN works well in those areas. In this paper, we propose using RNN with long short-term memory units for server load and performance prediction. Classical methods for performance prediction focus on building relation between performance and time domain, which makes a lot of unrealistic hypotheses. Our model is built based on events, which is (...) the root cause of server performance. We predict the performance of the servers using RNN-LSTM by analyzing the log of servers in data center which contains user’s access sequence. Previous work for workload prediction could not generate detailed simulated workload, which is useful in testing the working condition of servers. Our method provides a new way to reproduce user request sequence to solve this problem by using RNN-LSTM. Experiment result shows that our models get a good performance in generating load and predicting performance on the data set which has been logged in online service. We did experiments with nginx web server and mysql database server, and our methods can been easily applied to other servers in data center. (shrink)

Governments have adopted strict home quarantine measures during the COVID-19 pandemic. A monotonous, barren, and under-stimulating environment can cause state boredom, and people often deal with boredom via novelty-seeking behavior. Novelty-seeking behavior can be divided into “novelty input” and “novelty output.” The former refers to obtaining novel information such as browsing the Web; the latter refers to engaging in creative behavior such as literary creation. This study explores the relationship between two types of novelty-seeking behavior and individual state boredom during (...) home quarantine, along with the moderation effect of trait creativity. The study sample consists of 582 Chinese college students who were quarantined at home during the COVID-19 pandemic. Participants completed the Multidimensional State Boredom Scale, the Williams Creativity Aptitude Test, and self-compiled questionnaires of novelty input and novelty output. The results show that there is no significant relationship between novelty input or novelty output and boredom during the COVID-19 quarantine. Trait creativity is found to negatively moderate the relationship between the two means of novelty seeking and boredom. Specifically, novelty output negatively predicts the state boredom of individuals with high creativity, while novelty input positively predicts the state boredom of individuals with low creativity. Our findings suggest that different novelty-seeking behaviors may have different effects on the boredom level of individuals with high versus low creativity during quarantine. During a quarantine period, individuals should avoid excessively engaging in novelty input behaviors aimed at escaping boring situations. (shrink)

Chief executive officer tenacity plays an important role in corporate entrepreneurial activity. However, much less is known about its impact on employee intrapreneurship. Drawing from social information processing theory and upper echelons theory, this article examines the hitherto unexplored nexus between CEO tenacity and employee intrapreneurship, as well as the mediating role of corporate social responsibility. Quantitative data were collected through a survey administered to 294 employees working in different sectors that engage in CSR activities in China. Data analysis was (...) performed using hierarchical regression method through Stata 16.0. It was found that CEO tenacity was significantly positively correlated with employee strategic renewal behavior and employee venture behavior. The positive correlation between CEO tenacity and CSR was also significant. Besides, CSR partially mediated the relationship between CEO tenacity and employee strategic renewal behavior or employee venture behavior. This study extends research on CEO tenacity, CSR, or employee intrapreneurial behavior by providing a better understanding of the direct effects of CEO tenacity on employee intrapreneurial behavior and CSR. From the perspective of cross-fertilization between psychology and management, this study establishes the interface role of CSR by elucidating the intrinsic mechanism of CEOs with high levels of tenacity to stimulate employee intrapreneurial behavior through CSR. (shrink)

With the ongoing coronavirus disease 2019 pandemic, technological, socio-political, and institutional changes have led to a “new normal” competitive landscape, firms must make longer-term strategic changes to deal with short-term discontinuities and great uncertainties to acquire sustainable advantage. Based on regulatory focus theory and upper echelons theory, this study explores the relationship between CEO regulatory focus and corporate strategic change and examines the moderating effects of analysts’ optimism bias in earning forecasts. The study uses data from A-share-listed companies in China (...) during 2010–2018. We find that CEO promotion focus is positively associated with strategic change, while CEO prevention focus is negatively associated with strategic change. We also find analysts’ optimism bias in earning forecasts would moderate these relationships. (shrink)

It has been suggested that there is a close relationship between visual attention span (VAS) and fluent reading. This relation may be modulated by participants’ age, and exhibits various patterns in different reading modes (i.e. oral v.s. silent reading) and different reading levels (e.g. sentence v.s. character/word levels). Moreover, the modulation effects from the above factors might be more remarkable in the framework of languages with a deep orthography. Therefore, the present study investigated the developmental pattern of the relationship between (...) VAS skills and reading fluency in Chinese, a language with particularly deep orthography, by recruiting 292 participants from primary schools, middle schools and universities. Two tests were utilized to assess fluent reading skills at the single-character and sentence levels with oral and silent reading modes. A visual 1-back task was adopted to reflect VAS capacity with non-verbal stimuli and no verbal response. Results showed that the VAS capacity of low-grade primary school students could significantly account for the variance in single-character reading fluency in the oral mode and that it was a significant predictor of sentence reading fluency in the oral mode among high-grade primary school students. VAS abilities of middle school students allowed a unique and stable prediction of their silent sentence reading. With increasing reading ability, VAS skills of adults showed significant and similar predictive power for estimating the variations in fluent sentence reading in both silent and oral modes. These results revealed developmental changes in the contribution of VAS to fluent reading in Chinese, and provided evidence unveiling whether the underlying mechanisms of oral and silent reading were shared or different. (shrink)

Social-bots-mediated information manipulation is influencing the public opinion environment, and their role and behavior patterns in news proliferation are worth exploring. Based on the analysis of bots' posting frequency, influence, and retweeting relationship, we take the diffusion of The New York Times' coverage of Xinjiang issue on the overseas social platform Twitter as an example and employ the two-step flow model. It is found that in the role of second-step diffusion, unlike posting news indiscriminately in first-step diffusion, social bots are (...) more inclined to postcontroversial information in second-step diffusion; in terms of diffusion patterns, although social bots are more engaged in first-step diffusion than in second-step diffusion and can trigger human users to retweet, they are still inferior to humans in terms of influence. (shrink)

ObjectiveWhen regaining consciousness, patients who emerge from a minimally conscious state (EMCS) present with different levels of functional disability, which pose great challenges for treatment. This study investigated the frontoparietal activity in EMCS patients and its effects on functional disability.Materials and methodsIn this preliminary study, 12 EMCS patients and 12 healthy controls were recruited. We recorded a resting-state scalp electroencephalogram (EEG) for at least 5 min for each participant. Each patient was assessed using the disability rating scale (DRS) to determine (...) the level of functional disability. We analyzed the EEG power spectral density and sensor-level functional connectivity in relation to the patient’s functional disability.ResultsIn the frontoparietal region, EMCS patients demonstrated lower relative beta power (P < 0.01) and higher weighted phase lag index (wPLI) values in the theta (P < 0.01) and gamma (P < 0.01) bands than healthy controls. The frontoparietal theta wPLI values of EMCS patients were positively correlated with the DRS scores (rs = 0.629, P = 0.029). At the whole-brain level, EMCS patients only had higher wPLI values in the theta band (P < 0.01) than healthy controls. The whole-brain theta wPLI values of EMCS patients were also positively correlated with the DRS scores (rs = 0.650, P = 0.022). No significant difference in the power and connectivity between the frontoparietal region and the whole brain in EMCS patients was observed.ConclusionEMCS patients still experience neural dysfunction, especially in the frontoparietal region. However, the theta connectivity in the frontoparietal region did not increase specifically. At the level of the whole brain, the same shift could also be seen. Theta functional connectivity in the whole brain may underlie different levels of functional disability. (shrink)

This work is developed to explore the form of mental health education, strengthen scientific educational ideas, and improve the effect of psychological therapy. Virtual reality technology is innovatively applied in adolescent mental health treatment and education. Based on this, the mental health treatment and system design based on virtual reality technology are discussed, and the feasibility of applying VR technology to adolescent mental health education is explored. Second, the research concept of adolescent mental health is discussed. Based on the VR (...) platform setup, questionnaire survey is implemented to analyze the factors influencing the mental health of primary and secondary school students in Xi’an, Shaanxi Province, and five factors are obtained. Based on this, the adolescent mental health treatment system based on VR is designed, and the effectiveness of the system is tested and evaluated. The results show that the integrated delay of the VR equipment used is 29 ms, which can effectively provide service. There are significant differences in mental health status among adolescents of different genders, different ages, only children and non-only children, parents’ accompaniment during growing up, and urban and rural adolescents. Finally, after 3 months of psychological treatment, the mental health score of the experimental group of teenagers is 50–55 points. However, the mental health scores of the control group remain at 56–65 points, indicating that the mental health treatment system designed in this work can effectively help the adolescents to improve their mental health, thus proving the effectiveness of the system. To sum up, this work provides scientific reference for adolescent mental health education in schools. Psychological treatment system can help teenagers improve their psychological problems and promote the development of mental health education. (shrink)

Travel route preferences can strongly interact with the events that happened in networked traveling, and this coevolving phenomena are essential in providing theoretical foundations for travel route recommendation and predicting collective behaviour in social systems. While most literature puts the focus on route recommendation of individual scenic spots instead of city travel, we propose a novel approach named City Travel Route Recommendation based on Sequential Events Similarity by applying the coevolving spreading dynamics of the city tour networks and mine the (...) travel spatiotemporal patterns in the networks. First, we present the Event Sequence Similarity Measurement Method based on modelling tourists’ travel sequences. The method can help measure similarities in various city travel routes, which combine different scenic types, time slots, and relative locations. Second, by applying the user preference learning method based on scenic type, we learn from the user’s city travel historical data and compute the personalized travel preference. Finally, we verify our algorithm by collecting data of 54 city travellers of their historical spatiotemporal routes in the ten most popular cities from Mafeng.com. CTRR-SES shows better performance in predicting the user’s new city travel sequence fitting the user’s individual preference. (shrink)

Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for understanding the mechanism of programmed cell death, and their function is related to their types. According to the classification scheme by Zhou and Doctor (2003), the apoptosis proteins are categorized into the following four types: (1) cytoplasmic protein; (2) plasma membrane-bound protein; (3) mitochondrial inner and outer proteins; (4) other proteins. A powerful learning machine, the Support Vector Machine, is applied (...) for predicting the type of a given apoptosis protein by incorporating the sqrt-amino acid composition effect. High success rates were obtained by the re-substitute test (98/98 = 100 %) and the jackknife test (89/98 = 90.8%). (shrink)

本书收录论文17篇及附录三则,是汉语学术界第一部全面论述18世纪朝鲜阳明学者郑齐斗的专著,在东亚儒学研究中特别具有开拓新领域之意义。.

The impacts of COVID-19 have spread rapidly to global financial markets. In this context, combining the spillover index method introduced by Diebold and Yilmaz and the complex network analysis framework, we examined the volatility connectedness and the topological structure among the top ten cryptocurrencies before and during the COVID-19 crisis. The results revealed that the total volatility connectedness of the cryptocurrency market markedly increased following the outbreak of COVID-19; statically, Bitcoin, Ethereum, Cardano, and Bitcoin Cash were the net transmitters before (...) COVID-19, while Bitcoin, Ethereum, Ripple, Litecoin, Cardano, and Stellar became the major net transmitters in the market after COVID-19. Dynamically, the dynamic performance of different cryptocurrencies during the COVID-19 pandemic was heterogeneous, and the possible driving factors are diverse. Moreover, from network analysis, we further found that the COVID-19 crisis has significantly changed the topological structure of the cryptocurrency market. Our findings may help understand the typical dynamics in the cryptocurrency market and provide significant implications for portfolio managers, investors, and government agencies in times of highly stressful events like the COVID-19 crisis. (shrink)

In the real world, individual resources are crucial for patients when epidemics outbreak. Thus, the coupled dynamics of resource diffusion and epidemic spreading have been widely investigated when the recovery of diseases significantly depends on the resources from neighbors in static social networks. However, the social relationships of individuals are time-varying, which affects such coupled dynamics. For that, we propose a coupled resource-epidemic dynamic model on a time-varying multiplex network to synchronously simulate the resource diffusion and epidemic spreading in dynamic (...) social networks. The equilibrium analysis of the coupled model is conducted in a general scenario where the resource generation varies between susceptible and infected states and the recovery rate changes between resourceful and noresource states. By using the microscopic Markov chain approach and Monte Carlo simulations, we determine a probabilistic framework of the intralayer and interlayer dynamic processes of the coupled model and obtain the outbreak threshold of epidemic spreading. Meanwhile, the experimental results show the trivially asymmetric interactions between resource diffusion and epidemic spreading. They also indicate that the stronger activity heterogeneity and the larger contact capacity of individuals in the resource layer can more greatly promote resource diffusion, effectively suppressing epidemic spreading. However, these two individual characters in the epidemic layer can cause more resource depletion, which greatly promotes epidemic spreading. Furthermore, we also find that the contact capacity finitely impacts the coupled dynamics of resource diffusion and epidemic spreading. (shrink)

The transition of gene switch induced by external noises and external signals is investigated in the genetic regulatory system. Results show that the state-to-state transition of gene switch as well as resonant behaviors, such as the explicit coherence resonance, implicit coherence resonance and control parameter coherence biresonance, can appear when noises are injected into the genetic regulatory system. The ECR is increased with the increase of the control parameter value when starting from the supercritical Hopf bifurcation parameter point, and there (...) exists a critical control parameter value for the occurrence of ECR. However, the ICR is decreased as the control parameter value is increased when starting from the subcritical Hopf bifurcation point. In particular, the coherence of ECR is higher and more sensitive to noise than that of ICR. When an external signal is introduced into the system, the enhancement or suppression of the CPCBR and the number of peaks strongly depend on the frequency and amplitude of the external signal. Furthermore, the gene regulation system can selectively enhance or decrease the noise-induced oscillation signals at preferred frequency and amplitude of an external signal. (shrink)

We investigate how a broker firm’s initial public offering affects its analysts’ fiduciary duty of providing independent and objective recommendations. We find that the analysts of newly listed broker firms issue more positively biased recommendations in the first 2 to 3 years after their employers’ IPO than before the IPO. The increase in the recommendation bias is greater among analysts of affiliated brokers and brokers that raise additional capital after their IPO than among other analysts. Newly listed broker firms experience (...) significant increases in revenue and trading commission, and the increases are positively related to recommendation bias, after controlling for many other factors. More importantly, recommendation bias decreases as newly listed broker firms season and as the importance of trading commission declines. This suggests that public exposure through a broker firm’s IPO does not enhance the integrity and professional conduct of its financial analysts. Rather, economic incentives make financial analysts more accepting of unethical behavior. The overall results imply that the public trading of financial gatekeepers compromises the ethical relationship between financial service professionals and society in general. (shrink)

The genetic equidistance result shows that different species are approximately equidistant to a simpler outgroup in protein sequence similarity, as first reported by Margoliash in 1963. This result, together with those of Zuckerkandl and Pauling in 1962 inspired the molecular clock and in turn the neutral theory of evolution. Here it is shown that the clock/neutral theory had from the beginning overlooked another characteristic of the equidistance result, the overlap feature, which shows a large number of overlapped mutant amino acid (...) positions where any pair of any three species is different provided that the species concerned differ from one another in complexity as a result of macroevolution. In contrast, when simple organisms of similar complexity and short evolutionary divergence are compared, there are only a small number of overlaps largely consistent with chance or the neutral theory. The full reality of the equidistance result strongly supports the Maximum Genetic Diversity hypothesis, a more complete account of hereditary changes. (shrink)

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the (...) development of the community-based Coronavirus Infectious Disease Ontology in early 2020. -/- As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. -/- CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications. (shrink)