In the Original publication of the article the revised date was erroneously published as: 20 August 2017 the correct date is: 20 August 2020.

Incidental findings in research with human participants may have implications for a person’s present health or future health outcomes. Current guidelines focus on methods for handling and reporting incidental findings from biological test data but incidental findings might also arise from non-biological tests. This article presents three examples in which the results from non-biological test data can be predictive of future disease and should be disclosed to research participants. It is intended to increase awareness and facilitate further discussion about the (...) reporting of incidental findings from non-biological data. (shrink)

Examines the myriad ways contemporary residents of Beijing understand and nurture the good life, practice the embodied arts of everyday well-being, and in doing so draw on cultural resources ranging from ancient metaphysics to modern media.

This academic paper critically examines the incentive measures established by China to foster scientific innovation. The study explores China’s five key incentive measures, namely the pilot tenure-track system, monetary rewards for scientific publications, research awards for scientific achievements, "hat-talent" selection, and research funding system. The analysis also addresses the challenges associated with these measures, such as heightened work stress due to intense competition and occurrences of academic misconduct. In conclusion, two recommendations are proposed to enhance China’s incentive system: the establishment (...) of a responsible peer review system and the reduction of administrative power’s influence on scientists’ career trajectories. (shrink)

In recent years, more and more people are applying Convolutional Neural Networks to the study of sound signals. The main reason is the translational invariance of convolution in time and space. Thereby the diversity of the sound signal can be overcome. However, in terms of sound direction recognition, there are also problems such as a microphone matrix being too large, and feature selection. This paper proposes a sound direction recognition using a simulated human head with microphones at both ears. Theoretically, (...) the two microphones cannot distinguish the front and rear directions. However, we use the original data of the two channels as the input of the convolutional neural network, and the resolution effect can reach more than 0.9. For comparison, we also chose the delay feature (GCC) for sound direction recognition. Finally, we also conducted experiments that used probability distributions to identify more directions. (shrink)

Stephen Yablo’s notion of proportionality, despite controversies surrounding it, has played a significant role in philosophical discussions of mental causation and of high-level causation more generally. In particular, it is invoked in James Woodward’s interventionist account of high-level causation and explanation, and is implicit in a novel approach to constructing variables for causal modeling in the machine learning literature, known as causal feature learning (CFL). In this article, we articulate an account of proportionality inspired by both Yablo’s account of proportionality (...) and the CFL account of variable construction. The resulting account has at least three merits. First, it illuminates an important feature of the notion of proportionality, when it is adapted to a probabilistic and interventionist framework. The feature is that at the center of the notion of proportionality lies the concept of “determinate intervention effects.” Second, it makes manifest a virtue of (common types of) high-level causal/explanatory statements over low-level ones, when relevant intervention effects are determinate. Third, it overcomes a limitation of the CFL framework and thereby also addresses a challenge to interventionist accounts of high-level causation. (shrink)

Due to the advent of deglobalization and regional integration, this article aims to adopt LASSO-based network connectedness to estimate the multiscale tail risk spillover effects of global stock markets. The results show that tail risk varies across frequencies and shocks. In static analysis, the risk is centered mostly on the developed European and North American markets at a low frequency, and regionalization is imposed on the moderate frequency. Moreover, emerging markets could be sources of risk spillover, especially at the highest (...) frequency where there is no absolute risk center. In dynamic analysis, we use rolling window estimation and find that different frequencies identify distinct episodes of shocks, which provides us with the reason for the diverse risk centers at different time scales in static analysis. Our findings provide heterogeneous financial practitioners, regulators, and investors with diverse characteristics of stock markets under multiple time horizons and help them operate their own trading strategies. (shrink)

In this paper, a 3D jerk chaotic system with hidden attractor was explored, and the dissipativity, equilibrium, and stability of this system were investigated. The attractor types, Lyapunov exponents, and Poincare section of the system under different parameters were analyzed. Additionally, a circuit was carried out, and a good similarity between the circuit experimental results and the theoretical analysis testifies the feasibility and practicality of the original system. Furthermore, a robust feedback controller was designed based on the finite-time stability theory, (...) which guarantees the synchronization of 3D jerk master-slave system in finite time and asymptotically converges to the origin. Finally, we also give verification for the discussion in this paper by numerical simulation. (shrink)

The purpose of this study was to examine how culture shapes creativity by reviewing empirical findings across diverse studies. The impact of culture on creativity is typically manifested in three ways: (a) people from different cultures or settings have distinct implicit and/or explicit conceptions of creativity; (b) individuals from different cultures, particularly those from individualist and collectivist cultures, show differences in preferred creative processes and creative processing modes (e.g., usefulness seems more important than novelty in the East, whereas novelty seems (...) equally important as usefulness, if not more so, in the West) when they are engaged in creative endeavors; (c) creativity may be assessed using different measures based on culture-related contents or materials, and findings are accurate only when culturally appropriate or culturally fair measures are used. Potential implications and future directions are also proposed. (shrink)

Job shop scheduling problem is one of the most difficult optimization problems in manufacturing industry, and flexible job shop scheduling problem is an extension of the classical JSP, which further challenges the algorithm performance. In FJSP, a machine should be selected for each process from a given set, which introduces another decision element within the job path, making FJSP be more difficult than traditional JSP. In this paper, a variant of grasshopper optimization algorithm named dynamic opposite learning assisted GOA is (...) proposed to solve FJSP. The recently proposed dynamic opposite learning strategy adopts the asymmetric search space to improve the exploitation ability of the algorithm and increase the possibility of finding the global optimum. Various popular benchmarks from CEC 2014 and FJSP are used to evaluate the performance of DOLGOA. Numerical results with comparisons of other classic algorithms show that DOLGOA gets obvious improvement for solving global optimization problems and is well-performed when solving FJSP. (shrink)

Against the backdrop of COVID-19, the mental health of college students with financial difficulties deserves scientific attention. This paper on the relationship between mental resilience and the mental health of students with financial difficulties summarizes the research on the psychological resilience of students with financial difficulties during the COVID-19 pandemic. It also suggests ways in which to improve the mental health levels of students with financial difficulties by improving their mental resilience.

New Zealand is a multilingual and multicultural society, where English, Maori, and the New Zealand sign language are designated as its official languages. However, some heritage languages are also taught either within or outside the national education system. During the past decade, an increasing number of students have chosen Mandarin Chinese as an additional language because of its fast-growing importance. To date, studies regarding CAL are mainly based on the mainstream Chinese programs or online platforms, with less attention paid to (...) other types of teaching contexts where there also exist many potential challenges awaiting teachers. To fill in this gap, this study, based on a teaching program consisting of two families in New Zealand, explored the trajectories of a CAL teacher’s emotional labor for 47 weeks to understand how she managed her emotions when she taught the language as well as balanced the relationship among the three parties: the institution, the two families, and herself. Narrative inquiry was used as a methodological approach. The data involved written and spoken narratives. Using inductive and deductive thematic analysis, findings revealed her different understandings of the emotional labor in the two families, respectively, during the program. Further analysis of the data revealed some factors that impacted her emotional labor and how they impacted her teaching in a family-based context. We concluded our study with a discussion of the implications of these findings for teaching CAL in similar contexts. (shrink)

Differential leadership as a localized leadership style gradually developed on the basis of the Pattern of Differential Sequence. It plays a dual role in stimulating “insider subordinates” and “outsider subordinates” through the dynamic transformation of the roles. Using the process of game reasoning, the study identifies the differing principles used by insider subordinates and outsider subordinates in implementing deviant innovative behaviors. The simulation graph presents the perceived benefits of employees performing or not performing deviant innovative behaviors as clues during the (...) reasoning process, and implements deviant innovative behaviors for the high risk-taking trait of insider subordinates and the high internal control personality of outsider subordinates who implement deviant innovation. The theoretical derivation of behavior provides relevant references, and provides counter measures for effectively promoting employees’ deviant innovative behavior in the context of differential leadership. (shrink)

The Affymetrix GeneChip is a popular microarray platform for genome‐wide expression profiling and has been widely used in functional genomics especially in the classification of cancers. Due to the updating of genome data, much of the genome information with which the chips were designed is out‐of‐date and it has been reported that many of the genes/transcripts on the chips differ from their original definition when mapping the probes to the new genome information. Dai et al. have reported that the updated (...) definition can cause as much as 30–50% discrepancy in the genes selected as differentially expressed on a heart tissue expression profiling dataset. Understanding the nature of this difference is therefore very important for the utilization of the data. In this work, with a large cancer dataset as an example, we compared two major definitions and investigated their effects on classification, clustering, discovery of differentially expressed genes and gene‐set‐based analysis. Results show that the two definitions agree well on clustering and classification results but genes and gene sets discovered as differentially expressed or enriched can be very different. Discoveries based on the Affymetrix definition can cover most of those based on the new definition, but tend to have more false positives. BioEssays 28: 739–746, 2006. © 2006 Wiley Periodicals, Inc. (shrink)

ABSTRACT This paper aims to provide a comprehensive insight into the role of mindfulness in organizational settings. A daily experience sampling method was used to explore the mechanism through which state mindfulness influences employees’ work attentiveness. By collecting data from 153 full-time Chinese employees over 5 consecutive days, we used 765 matched cases to conduct a multilevel structural equation model with random slopes to test the conceptual model. The results showed that: 1) daily state mindfulness is positively related to employee (...) work attentiveness; 2) employee moral self-efficacy mediates the indirect relationship between daily state mindfulness and work attentiveness; and 3) moral disengagement moderates the indirect relationship between state mindfulness and work attentiveness through moral self-efficacy, such that the indirect relationship will be weaker in the condition of low moral disengagement than in the condition of high moral disengagement. This research contributes to the work attentiveness literature by incorporating state mindfulness as a critical antecedent. (shrink)

The web is being loaded daily with a huge volume of data, mainly unstructured textual data, which increases the need for information extraction and NLP systems significantly. Named-entity recognition task is a key step towards efficiently understanding text data and saving time and effort. Being a widely used language globally, English is taking over most of the research conducted in this field, especially in the biomedical domain. Unlike other languages, Arabic suffers from lack of resources. This work presents a BERT-based (...) model to identify biomedical named entities in the Arabic text data that investigates the effectiveness of pretraining a monolingual BERT model with a small-scale biomedical dataset on enhancing the model understanding of Arabic biomedical text. The model performance was compared with two state-of-the-art models, and it outperformed both models with 85% F1-score. (shrink)

There are differences in caregivers’ literacy and health literacy levels that may affect their ability to consent to children participating in clinical research trials. This study aimed to explore the effectiveness, and caregivers’ understandings, of the process of informed consent that accompanied their child’s participation in a dental randomized control trial (RCT). Telephone interviews were conducted with a convenience sample of ten caregivers who each had a child participating in the RCT. Pre-tested closed and open-ended questions were used, and the (...) findings were produced from an inductive analysis of the latter and a descriptive analysis of the former. Participants had limited understanding of the purpose of the RCT and rated the readability of the consent form more highly than they rated their understanding of the research. All felt that informed consent was vital, but some caregivers had not read the consent documents. Some caregivers enrolled their child in the RCT because they trusted the researchers, and the majority wanted to improve dental care for children. The informed consent process was not always effective despite high readability of the informed consent documents. Researchers must consider the health literacy of the study group, and actively engaging with caregivers to achieve meaningful informed consent may be challenging. Future research could explore participants’ perspectives of informed consent in populations with low health literacy and assess whether an underlying expectation not to comprehend health-related information may be a barrier to informed consent. (shrink)

Several previous studies have reported atypicality in resting-state functional connectivity in autism spectrum disorder, yet the relatively small effect sizes prevent us from using these characteristics for diagnostic purposes. Here, canonical correlation analysis and hierarchical clustering were used to partition the high-functioning ASD group into subgroups. A support vector machine model was trained through the 10-fold strategy to predict Autism Diagnostic Observation Schedule scores within the ASD discovery group, which was further validated in an independent sample. The neuroimage-based partition derived (...) two subgroups representing severe versus mild autistic patients. We identified FCs that show graded changes in strength from ASD-severe, through ASD-mild, to controls, while the same pattern cannot be observed in partitions based on ADOS score. We also identified FCs that are specific for ASD-mild, similar to a partition based on ADOS score. The current study provided multiple pieces of evidence with replication to show that resting-state functional magnetic resonance imaging FCs could serve as neural biomarkers in partitioning high-functioning autistic individuals based on their symptom severity and showing advantages over traditional partition based on ADOS score. Our results also indicate a compensatory role for a frontocortical network in patients with mild ASD, indicating potential targets for future clinical treatments. (shrink)

This research has purpose to take local woven or “Pahkahmah” which is a cultural product of the local woven of Nong Kao district in Kanchanaburi province of Thailand to develop for and applying with contemporary fashion design in order to increase its value. The process of creation in this research has 5 steps as 1. Create concept and inspiration 2. Design collections for the improved textiles 3. Create decoration technique for the improved textile and collections 4. Create the prototype collections (...) and products 5. Evaluate satisfactory for the prototype collection and products. The improved textiles were used in making 3 collections of fashion apparels and costume accessories in street fashion for present lifestyle. Knowledge to improved and develop local Pahkahmah woven textile and the idea from prototype collections and products from this research was relayed to makers of Pahkahmah woven textile in Nong Kao district, Kanchanaburi province. Evaluation for satisfactory to the creative idea and developed textile products by representatives of Pahkahmah woven textile maker community and consumers revealed average score 4.45 with standard deviation 0.27. Knowledge from this research become a guideline for sustainable development and innovative idea for increasing commercial value to the local Pahkahma woven products of Nong Kao district community. (shrink)

Brain lateralization of lexical tone processing remains a matter of debate. In this study we used a dichotic listening paradigm to examine the influences of the knowledge of Jyutping, linguistic-processing demand and tone type on the ear preference pattern of native tone processing in Hong Kong Cantonese speakers. While participants with little knowledge of Jyutping showed a previously reported left-ear advantage, those with a good level of Jyutping expertise exhibited either a right-ear advantage or bilateral processing during lexical tone identification (...) and contour tone discrimination, respectively. As for the effect of linguistic-processing demand, while an LEA was found in acoustic/phonetic perception situations, this advantage disappeared and was replaced by a bilateral pattern in conditions that involved a greater extent of linguistic processing, suggesting an increased involvement of the left hemisphere. Regarding the effect of tone type, both groups showed an LEA in level tone discrimination, but only the Jyutping group demonstrated a bilateral pattern in contour tone discrimination. Overall, knowledge of written codes of tones, greater degree of linguistic processing and contour tone processing seem to influence the brain lateralization of lexical tone processing in native listeners of Cantonese by increasing the recruitment of the left-hemisphere language network. (shrink)

Kindergarten climate has been reported to be closely associated with teachers' retention intention, yet the underlying mechanism of this association remains unclear in some ethnic minority areas in China. Based on the Personal-Environment Fit Theory and Organizational Support Theory, the research aims to examine the correlation between kindergarten climate and retention intention of Chinese kindergarten teachers in ethnic minority areas and the chain mediating role of perceived organizational support, as well as the psychological empowerment. In total, 1,199 Chinese kindergarten teachers (...) were recruited from ethnic minority areas to complete the questionnaires. Based on their responses, the main findings of the study were listed as follows: A supportive kindergarten climate has a positive correlation with perceived organizational support, psychological empowerment, and retention intention. A positive kindergarten climate would increase the retention intention only through the indirect path of perceived organizational support, psychological empowerment, as well as the chain mediating path between these two variables. Taken together, these results further explained the interplay between kindergarten climate and teachers' retention intention. Implications for research on retention intention were discussed. Theoretically, it enriches the theoretical basis related to the external environmental resources and individual cognition. Practically, it means that educational policymakers will need to issue new guidelines to ensure that more kindergarten teachers are retained in China's ethnic minority areas. (shrink)

The issue of employability has already become a well-delineated topic of study among interpreting educators. However, the current literature still lacks descriptive research on interpreting students' employability development and ignores the developmental effects of interpreter competences in this process. Moreover, the advantage of using career adaptability for measurement is also under-researched. This exploratory case study aims at taking an initial step forward, surveying interpreting students' career adaptability development and the developmental effects of different interpreter competences on major adaptability resources, and (...) ultimately diagnosing curriculum problems and making modifications accordingly. Thirty grade 2019 interpreting students from three Chinese universities contributed to data collection, through six questionnaires in a two-wave survey. The results highlight that, throughout the Chinese MTI program, interpreting students could become more concerned and well prepared for their future, more curious to explore themselves and their surroundings, and more capable of solving problems. The results also indicate that students' knowledge and language competence serve as the major facilitators in this process, and that other interpreter competences, such as psychological competence, transfer competence, professionalism, and cross-cultural competence, are also instrumental. In order to further boost their adaptability constructs, the results suggest that students' language and knowledge competence, professionalism, and cross-cultural and mental agility still need to be improved. Five suggestions for curriculum revision have been raised accordingly. As an initial effort, the current study will hopefully inspire further studies on interpreting students' career adaptability and add more knowledge to the curriculum design from this viewpoint. (shrink)

Current development in a deep neural network has given an opportunity to a novel framework for the reconstruction of a holographic image and a phase recovery method with real-time performance. There are many deep learning-based techniques that have been proposed for the holographic image reconstruction, but these deep learning-based methods can still lack in performance, time complexity, accuracy, and real-time performance. Due to iterative calculation, the generation of a CGH requires a long computation time. A novel deep generative adversarial network (...) holography framework is proposed for hologram reconstruction. This novel framework consists of two phases. In phase one, we used the Fresnel-based method to make the dataset. In the second phase, we trained the raw input image and holographic label image data from phase one acquired images. Our method has the capability of the noniterative process of computer-generated holograms. The experimental results have demonstrated that the proposed method outperforms the existing methods. (shrink)

Context. Social media platforms such as Facebook and Twitter carry a big load of people’s opinions about politics and leaders, which makes them a good source of information for researchers to exploit different tasks that include election predictions. Objective. Identify, categorize, and present a comprehensive overview of the approaches, techniques, and tools used in election predictions on Twitter. Method. Conducted a systematic mapping study on election predictions on Twitter and provided empirical evidence for the work published between January 2010 and (...) January 2021. Results. This research identified 787 studies related to election predictions on Twitter. 98 primary studies were selected after defining and implementing several inclusion/exclusion criteria. The results show that most of the studies implemented sentiment analysis followed by volume-based and social network analysis approaches. The majority of the studies employed supervised learning techniques, subsequently, lexicon-based approach SA, volume-based, and unsupervised learning. Besides this, 18 types of dictionaries were identified. Elections of 28 countries were analyzed, mainly USA and Indian elections. Furthermore, the results revealed that 50% of the primary studies used English tweets. The demographic data showed that academic organizations and conference venues are the most active. Conclusion. The evolution of the work published in the past 11 years shows that most of the studies employed SA. The implementation of SNA techniques is lower as compared to SA. Appropriate political labelled datasets are not available, especially in languages other than English. Deep learning needs to be employed in this domain to get better predictions. (shrink)