H. C. B. Liu

In accordance with the compositionality criterion and hierarchy principle of Rhetorical Structure Theory, this study reframes each tree in the RST Discourse Treebank into three new dependency trees with ultimate nodes being clauses, sentences, and paragraphs, respectively, which also draw on an analogy between syntactic and discourse trees. Detailed percentages of various RST relations at the three granularity levels are examined, illuminating the discourse processes of organizing units of one granularity level into those of the next upper level and suggesting certain homogeneity and interaction across levels in the Treebank, particularly at the two upper levels. The study demonstrates the applicability of RST analysis between same-level terminal units. With unique analytical advantages, the newly constructed discourse dependency trees provide new research prospects.

Long distance travel is an unusual activity for humans. The economical cabin environment during the long haul flights causes discomfort and even stress for many passengers. In-flight video and music systems are commonly available to improve the comfort level of the passengers. However, current in-flight music systems do not explore how the content can be used to reduce passengers stress. Most of these systems are designed and implemented assuming a homogeneous passenger group that has similar tastes and desires. In this paper, we present a heart rate controlled in-flight music recommendation system for reducing the stress during air travel. The system recommends personalized music playlists to the passengers and attempts to keep their heart rate in a normal range with these playlists. Experiments in a simulated long haul flight cabin environment find that the passengers’ stress can indeed be significantly reduced through listening to the recommended music playlists.

Artificial intelligence (AI) is increasingly expected to disrupt the ordinary functioning of society. From how we fight wars or govern society, to how we work and play, and from how we create to how we teach and learn, there is almost no field of human activity which is believed to be entirely immune from the impact of this emerging technology. This poses a multifaceted problem when it comes to designing and understanding regulatory responses to AI. This article aims to: (i) defend the need for a novel conceptual model for understanding the systemic legal disruption caused by new technologies such as AI; (ii) to situate this model in relation to preceding debates about the interaction of regulation with new technologies (particularly the ‘cyberlaw’ and ‘robolaw’ debates); and (iii) to set out a detailed model for understanding the legal disruption precipitated by AI, examining both pathways stemming from new affordances that can give rise to a regulatory ‘disruptive moment’, as well as the Legal Development, Displacement or Destruction that can ensue. The article proposes that this model of legal disruption can be broadly generalisable to understanding the legal effects and challenges of other emerging technologies.

Rosalind Husthouse’s argumentation for the objectivity of virtue ethics includes three sub-arguments. But her explanations are problematic, because the “objectivity” argument does not have sufficient perspicuity, nor have abundant explanatory persuasion. In comparison with the perspicuity of structure in her work On Virtue Ethics, the three concerning explanations appear more obscure. And such obscurity results in her distinction of the three propositions being groundless, and the effect of her explanations lower than expected. Therefore, argumentation for the objectivity of virtue ethics should use another approach.

This study investigated the effect of non-task language in language switching experiment. Non-task language refers to participants’ language(s) (regardless of proficiency level) that are not used in any trials throughout the experiment. We recruited 60 Tibetan-Chinese-English trilinguals (grade-12 high school students with a median age of 17) to perform a lexical decision (word vs. non-word) task in only two of their languages. We repeated the experiment three times to present each language pair once. In each experiment, the participants were divided into two groups which significantly contrasted with each other in their non-task language while remained comparable in the two task languages. Response time (RT) and error rate (ER) have been examined to evaluate task performance. The interaction between task performance and the participants’ proficiency in the non-task language was also examined. The results showed null effect of language switching. In addition, the effect of the non-task language was not found. These results were interpreted with reference to the main models of bilingual visual word recognition and the role of orthography specificity.

This paper will investigate the roots of intentionality in Aristotle’s theory of perception and assess the accuracy of Brentano’s proposed location of intentionality in Aristotle. When introducing intentionality into contemporary philosophy, Brentano attributed it to Aristotle, whose theory of psychology he believed to reveal the characteristics of intentional inexistence. After setting up a working definition of intentionality that stresses such features as immanent content and intentional directedness, I will then clarify Aristotle’s theory of perception with regard to these two characteristics. I draw the conclusion that we can only find the roots of immanent content in Aristotle’s perceptual theory. For him, directedness moves from the sensible object to the sensitive soul, and thus it does not correspond to what contemporary philosophers define as intentional directedness.

The purposes of research were to describe the neonatal clinicians' personal views and attitudes on neonatal ethical decision-making, to identify factors that might affect these attitudes and to compare the attitudes between neonatal physicians and neonatal nurses in Taiwan. Research was a cross-sectional design and a questionnaire was used to reach different research purposes. A convenient sample was used to recruit 24 physicians and 80 neonatal nurses from four neonatal intensive care units in Taiwan. Most participants agreed with suggesting a do not resuscitate (DNR) order to parents for dying neonates (86.5%). However, the majority agreed with talking to patients about DNR orders is difficult (76.9%). Most participants agree that review by the clinical ethics committee is needed before the recommendation of ‘DNR’ to parents (94.23%) and nurses were significantly more likely than physicians to agree to this (p=0.043). During the end-of-life care, most clinicians accepted to continue current treatment without adding others (70%) and withholding of emergency treatments (75%); however, active euthanasia, the administration of drug to end-of-life, was not considered acceptable by both physicians and nurses in this research (96%). Based on our research results, providing continuing educational training and a formal consulting service in moral courage for neonatal clinicians are needed. In Taiwan, neonatal physicians and nurses hold similar values and attitudes towards end-of-life decisions for neonates. In order to improve the clinicians' communication skills with parents about DNR options and to change clinicians' attitudes for providing enough pain-relief medicine to dying neonates, providing continuing educational training and a formal consulting service in moral courage are needed

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.