Lin Hao

Palm-up (PU) is among the most frequent manual forms across signed languages, yet its functional range and form-function mapping remain poorly understood. This study presents a corpus-based analysis of PU in Chinese Sign Language (CSL), drawing on 793 tokens from 15.6 h of naturalistic interaction across three generations of signers. All tokens were coded for function, handshape, movement, clausal position, and non-manual features. PU in CSL is restricted to three functional domains: negation (61 %), discourse marking (28 %), and interrogation (11 %), which together account for 100 % of the corpus with no propositional functions attested. Each domain is associated with a stable bundle of formal features, forming a gradient from context-dependent discourse uses to morphologically bound affixal forms. Age-based analysis shows that the functional inventory is stable across cohorts while internal weighting has shifted, reflecting differential entrenchment consistent with ongoing grammaticalization. These findings support the view that PU is specialized for intersubjective meaning, managing cognitive coordination between signer and addressee, and that this specialization reflects both the iconic, addressee-directed properties of the open-palm form and the conventionalization history of individual signing communities.

It has been argued in previous research that several competing pressures guide the directions of language evolution (economy vs. redundancy; arbitrariness vs. systematicity). For sign languages, however, the effects of competing pressures on their change of lexical systems remain largely unclear. In the present study, we focus on the diachronic change in form and formational‐semantic systematicity of the Chinese Sign Language (CSL) lexicon. Drawing on two CSL lexicons (one from the 1960 dictionary and the other from the 2019 dictionary), we found that in the dimension of form, the CSL lexical system shows a trend toward monosyllabicity and symmetry. In terms of formational‐semantic systematicity, we found that there is a significant correlation between form and meaning in both lexicons, but the effect of the arbitrariness constraint gets stronger over time. Our findings regarding the change in form indicate that the competing pressures between economy and redundancy have different effects on different parameters when shaping the lexical system of CSL. As for the correlation between form and meaning, our study provides insight as to how a balance between arbitrariness and systematicity is reached.

Apoptosis proteins play an essential role in regulating a balance between cell proliferation and death. The successful prediction of subcellular localization of apoptosis proteins directly from primary sequence is much benefited to understand programmed cell death and drug discovery. In this paper, by use of Chou’s pseudo amino acid composition , a total of 317 apoptosis proteins are predicted by support vector machine . The jackknife cross-validation is applied to test predictive capability of proposed method. The predictive results show that overall prediction accuracy is 91.1% which is higher than previous methods. Furthermore, another dataset containing 98 apoptosis proteins is examined by proposed method. The overall predicted successful rate is 92.9%

Students often face difficulties and experience negative emotions toward second language learning. The affective tutoring system is a next-generation learning approach that can detect the affective status of learning to increase performance. Therefore, for the purposes of this study, an innovative affective mobile language tutoring system was designed to support Japanese language learning. The effects of AMLTS, along with asynchronous discussion, that were intended to improve performance, were examined using a triangulation method. To investigate the effect on emotion, the proposed AMLTS provides a virtual emotion agent that can interact with users and record emotional events, learning assessments, and the results of the interaction into a database. Learning effectiveness evaluations were conducted via two experiments: prototype evaluation and final evaluation. Sixty-three students, all beginners, were invited to use the AMLTS to learn Japanese. The research results show that the proposed AMLTS affective interaction design significantly improves learner engagement and performance. In the emotion feedback analysis and learning process, AMLTS helped students deepen their understanding of the content, enabled them to clearly understand the content, and to engage in peer interaction and experience positive emotions. In the evaluation of system usability, AMLTS reveals good usability for foreign language acquisition.

The prediction of the secondary structure of a protein from its amino acid sequence is an important step towards the prediction of its three-dimensional structure. However, the accuracy of ab initio secondary structure prediction from sequence is about 80 % currently, which is still far from satisfactory. In this study, we proposed a novel method that uses binomial distribution to optimize tetrapeptide structural words and increment of diversity with quadratic discriminant to perform prediction for protein three-state secondary structure. A benchmark dataset including 2,640 proteins with sequence identity of less than 25 % was used to train and test the proposed method. The results indicate that overall accuracy of 87.8 % was achieved in secondary structure prediction by using ten-fold cross-validation. Moreover, the accuracy of predicted secondary structures ranges from 84 to 89 % at the level of residue. These results suggest that the feature selection technique can detect the optimized tetrapeptide structural words which affect the accuracy of predicted secondary structures.