In order to establish the link between rehabilitation experience and patients' emotional feedback to assist decision-making in wrist rehabilitation program, this paper integrates gamified experience and proposes affective evaluation method based on cascaded fuzzy reasoning. Primarily, gamified interactive tasks are developed for wrist rehabilitation training, and the prototype of rehabilitation interactive system is built to collect multi-dimensional physiological signals (MPS). Subsequently, with MPS as input and arousal valence (AV) as output, fuzzy reasoning rule I is defined to establish MPS-AV model and calculate the value of AV. Besides, with AV as input and emotion label (EL) as output, fuzzy reasoning rule II is defined to establish AV-EL model and visually analyze the emotional state of patients. Lastly, the task completion rate of rehabilitation interaction behavior are calculated based on behavior coding, and the effectiveness of the proposed affective evaluation method is verified by integrating subjective evaluation. The gamified rehabilitation experience and the affective evaluation method based on cascaded fuzzy reasoning provide methods and experiences for wrist rehabilitation related products and services, and this protocol can also be generalized in the field of rehabilitation digital therapy.

Anecdotal evidence of cannabis use by professional programmers abounds. Recent studies have found that some professionals regularly use cannabis while programming, even for work-related tasks. However, accounts of the impacts of cannabis on programming vary widely and are often contradictory. For example, some programmers claim that it impairs their ability to generate correct solutions, while others claim it enhances creativity and focus. There remains a need for an empirical understanding of the true impacts of cannabis on programming. This paper presents the first controlled observational study of cannabis's effects on programming ability. Based on a within-subjects design with over 70 participants, we find that, at ecologically valid dosages, cannabis significantly impairs programming performance. Programs implemented while high contain more bugs and take longer to write (p < 0.05) --- a small to medium effect (0.22 ≤ d ≤ 0.44). We also did not find any evidence that high programmers generate more divergent solutions. However, programmers can accurately assess differences in their programming performance (r = 0.59), even when under the influence of cannabis. We hope that this research will facilitate evidence-based policies and help developers make informed decisions regarding cannabis use while programming.

Traditional Chinese medicine (TCM) has accumulated amount of literature with a total of 1,059 volumes, more than 190,000 chapters, and more than 120,000,000 words during the last 2000 years. In the previous works, researchers annotated the phrases one by one with their own hands. Here we propose semantic annotation techniques based on Semantic units division and annotation are realized through constructing a corpus and professional semantic unit dictionary. Based on the technology, a semantic annotation method is implemented using hidden markov models, which achieves 92.2% in terms of micro-average F1 measure and 87.6% in terms of macro-average F1 measure on the case of spleen putty genre.

Basis pursuit algorithm is one of the most popular methods of sparse coding. The goal of the algorithm is to represent signal using as few coefficients as possible, which is suitable for acoustic signal compression. This paper presents a lossless coding/decoding method using the basis pursuit algorithm. In this method, wavelet packets bases were used to compose the dictionary because of their natural sparse property. Experimental results are obtained by comparing the proposed method with the four popular lossless coding/decoding methods using various types of acoustic signals. The results show that the proposed method is competitive with the well-known methods for lossless compression, in terms of compression ratio and computational efficiency.

The customerpsilas privacy may be exposed in most existing micropayment schemes. To protect the privacy of a customerpsilas identity, according to the definitions of anonymity given in this paper, a novel micropayment scheme (called xPay) with security, efficiency and complete anonymity is proposed. The scheme, based on hash chain, introduces both the debit-based payment mode and the pseudonym mechanism using prepaid cards, with the purpose of complete anonymity. In addition, in order to control the operation cost, a lower bound of the requesting coin quantity during one exchange, redemption or transfer procedure is specially set, and this setting is employed in the xPay scheme.