H. C. B. Liu

Biomedical ontologies are emerging as critical tools in genomic and proteomic research where complex data in disparate resources need to be integrated. A number of ontologies exist that describe the properties that can be attributed to proteins; for example, protein functions are described by Gene Ontology, while human diseases are described by Disease Ontology. There is, however, a gap in the current set of ontologies—one that describes the protein entities themselves and their relationships. We have designed a PRotein Ontology (PRO) to facilitate protein annotation and to guide new experiments. The components of PRO extend from the classification of proteins on the basis of evolutionary relationships to the representation of the multiple protein forms of a gene (products generated by genetic variation, alternative splicing, proteolytic cleavage, and other post-translational modification). PRO will allow the specification of relationships between PRO, GO and other OBO Foundry ontologies. Here we describe the initial development of PRO, illustrated using human proteins from the TGF-beta signaling pathway.

Tactile emotion recognition provides a lot of valuable information in human-computer interaction, and it has strong application prospects in many aspects such as smart home and medical treatment. So this situation raises a question: How to quickly and efficiently let the robot perform the correct emotion recognition? In this work, we develop a lifelong learning algorithm which is based on the efficient dictionary learning technology, to tackle the tactile emotion recognition across different tasks. To verify the efficiency of the proposed method, we applied it to two data sets for experimentation: Corpus of Social Touch (CoST) and our dataset(We built it with a 12X12 array sensor). The results show that the proposed lifelong learning algorithm achieves satisfactory results.

As one of the important 21st-century skills, collaborative problem solving (CPS) has caught much attention in the assessment area. Two initiative approaches have been created: the human-to-human and human-to-agent modes. Between the two modes, the human-to-human interaction is much closer to the real-world situation and its process stream data can reveal more detailed information about the cognitive processes. In order to measure CPS ability effectively by this mode, how to extract indicators from the data and model it is crucial, while the existing methods all have some disadvantages. In the present study, we proposed a new paradigm for extracting indicators and modeling the dyad data in the human-to-human mode. Specifically, both individual and group indicators were extracted from the data stream, which served as evidence for demonstrating CPS skills. In addition, a within-item multidimensional Rasch model was used to fit the dyad data. To test the validity of the paradigm, we developed five tasks following the asymmetric mechanism and integrated them into an online testing platform. Four hundred thirty-four students from China participated in the assessment and the online platform recorded their crucial actions with time stamps. The new paradigm was used to deal with the generated process stream data. Results showed that the model fitted well. The item parameter estimates and fitting indexes were acceptable, and students were well differentiated. In general, the new paradigm of extracting indicators and modeling the dyad data is feasible for improving the human-to-human assessment of CPS. Finally, the limitations of the current study and further research directions are discussed.

Drawing on justice theory and upper echelons perspective, this study develops and tests an integrative model linking justice to the implementation of IT-enabled supply chain information integration through the top management. Specifically, the study investigates the effects of the three facets of justice—distributive, procedural, and interactional justice—on the two dimensions of IeSCII, and examines the mediating influences of top management beliefs and top management participation in these relationships. Using structural equation modeling to analyze data collected from 190 firms in China, the study documents that interactional justice positively affects both TMB and TMP, while procedural justice positively affects TMB in the IeSCII implementation process. In contrast, distributive justice is not significantly related to either TMB or TMP, but is positively associated with information sharing. The results also show that procedural justice positively affects TMB, which then positively affects TMP in IeSCII. Furthermore, the study finds significant mediating effects of TMB and TMP in the relationship between interactional justice and IeSCII. The theoretical and managerial implications of this study are discussed.

Whilst previous studies indicate perceived company ethicality as a driver of job seekers’ job-pursuit intentions, it is poorly understood how and why ethical market signals actually affect their application decisions. Perceptions of company ethicality result from market signals that are either within the control of the company and from market signals that are beyond the company’s control. Building on communication and information processing theories, this study therefore considers both types of ethical market signals, and examines the psychological mechanisms through which they affect job seekers’ intention to apply for a job. The results from a controlled online experiment show that both types of ethical market signals increase job seekers’ job-pursuit intentions. These relationships are mediated by applicants’ attitude towards the job advertisement, their perceptions of corporate employment image and self-referencing. Consequently, the present study alerts practitioners to consider the effects of company-controlled and non-company-controlled ethical market signals, particularly when aiming to recruit highly-qualified millennial candidates.

A superheterodyne receiver is a type of device universally used in a variety of electronics and information systems. Fault detection and diagnosis for superheterodyne receivers are therefore of critical importance, especially in noise environments. A general purpose fault detection and diagnosis scheme based on observers and residual error analysis was proposed in this study. In the scheme, two generalized regression neural networks are utilized for fault detection, with one as an observer and the other as an adaptive threshold generator; faults are detected by comparing the residual error and the threshold. Then, time and frequency domain features are extracted from the residual error for diagnosis. A probabilistic neural network acts as a classifier to realize the fault diagnosis. Finally, to mimic electromagnetic environments with noise interference, simulation model under different fault conditions with noise interferences is established to test the effectiveness and robustness of the proposed fault detection and diagnosis scheme. Results of the simulation experiments proved that the presented method is effective and robust in simulated electromagnetic environments.

We investigate how short and long-range word length correlations evolve in Chinese narrative texts. The results show that, for short-range word length correlations, no significant linear evolutionary trend was found. But for long-range correlations, there are two opposite tendencies for two different regimes: the Hurst exponent of small-scale word length correlations decreases over time, and the exponent of large-scale shows an increasing tendency. The increase of word length is corroborated as an essential regularity of word evolution in written Chinese. Further analyses show that a significant correlation coefficient is obtained between Hurst exponents from the small-scale correlations and mean word length across time. These indicate that word length correlation evolution possesses different self-adaptive mechanisms in terms of different scales of distances between words. We speculate that the increase of word length and sentence length in written Chinese may account for this phenomenon, in terms of both the social-cultural aspects and the self-adapting properties of language structures.

This article examines the role of metapragmatic expressions in constructing common ground in the call taker’s responses to customer direct complaints in telephone interactions in the framework of the socio-cognitive approach proposed and developed by Kecskes and Kecskes and Zhang. Based on five extracts drawn from the data of about two hours of 15 recordings of telephone interactions that include successful complaint settlements made between customers and the customer service department of one Chinese airline, it reveals that the call taker mainly employs five types of MPEs as CG construction devices to explicitly manifest intentions of giving accounts and explanations, confirming and checking information, negotiating adequate compensations, establishing close interpersonal relationships, and aligning with the organization. This article enhances our understanding of the functioning process of metapragmatic indicators in complaint settlement in institutional telephone interactions.