Effect of acoustic and linguistic contexts on human and machine speech recognition

We compared the performance of an automatic speech recognition system using n-gram language models, HMM acoustic models, as well as combinations of the two, with the word recognition performance of human subjects who either had access to only acoustic information, had information only about local linguistic context, or had access to a combination of both. All speech recordings used were taken from Japanese narration and spontaneous speech corpora.Humans have difficulty recognizing isolated words taken out of context, especially when taken from spontaneous speech, partly due to word-boundary coarticulation. Our recognition performance improves dramatically when one or two preceding words are added. Short words in Japanese mainly consist of post-positional particles (i.e. wa, ga, wo, ni, etc.), which are function words located just after content words such as nouns and verbs. So the predictability of short words is very high within the context of the one or two preceding words, and thus recognition of short words is drastically improved. Providing even more context further improves human prediction performance under text-only conditions (without acoustic signals). It also improves speech recognition, but the improvement is relatively small.Recognition experiments using an automatic speech recognizer were conducted under conditions almost identical to the experiments with humans. The performance of the acoustic models without any language model, or with only a unigram language model, were greatly inferior to human recognition performance with no context. In contrast, prediction performance using a trigram language model was superior or comparable to human performance when given a preceding and a succeeding word. These results suggest that we must improve our acoustic models rather than our language models to make automatic speech recognizers comparable to humans in recognition performance under conditions where the recognizer has limited linguistic context.     

中国经济增长要素分析：1978～2012

改革开放三十年来,物质资本要素是中国经济主要的增长动力,并且重要性逐渐上升;人力资本增长动力在1982年左右达到峰值,此后不断下降;劳动力增长动力在1988年达到峰值,此后也不断下降;全要素生产率呈倒“w”型增长轨迹,三次TFP的快速增长都与中国几次重要的经济制度变迁有着重要联系。在1978年～2012年间,经济体制改革、对外开放、基础设施建设、研发对TFP的解释存在变动,不同时期对TFP的解释力度不同。本文预测2013年～2020年,物质资本、人力资本、TFP增长动力将有所下降,经济潜在增长率将会下降到6％～8％之间。在未来十年,中国潜在经济增长速度将会下滑。     

稳定表达HIV-1病毒样颗粒的293细胞系的筛选及其稳定性

目的获得高效、稳定表达含有HIV-1主要结构蛋白gag、pol和env的病毒样颗粒的293细胞系。方法选择合适的真核细胞表达质粒与带有抗性基因的载体,共转染293真核细胞,用含有抗性的培养基筛选出稳定表达细胞株。结果HIV-1的gag、pol和env蛋白均在293细胞中获得了表达,且不同代次的293细胞中蛋白表达情况无明显差异。结论成功筛选了稳定表达HIV-1病毒样颗粒的293细胞系,为进一步开发艾滋病疫苗奠定了基础。     

人体β-防御素-3突变基因的克隆及在大肠杆菌中的表达

目的对人体β-防御素-3基因进行定点突变,并在E.coli中表达。方法从人正常皮肤组织中提取总RNA,经RT-PCR扩增编码β-防御素-3成熟肽的cDNA,测序正确后,设计含突变位点的引物,用PCR重叠延伸法对β-防御素-3成熟肽cDNA进行定点突变,将突变产物克隆至pUC18,并在E.coli中融合表达。结果测序结果表明,经RT-PCR所得的β-防御素-3成熟肽序列与GenBank中报道的序列完全一致。经过突变,β-防御素-3成熟肽第29位谷氨酰胺密码子由CAG突变为精氨酸密码子CGA,其余核苷酸序列均未发生变化。将突变β-防御素-3基因在E.coli中诱导表达后,可见突变β-防御素-3蛋白表达。结论已成功克隆并表达了β-防御素-3突变体基因。     

A framework for the assessment of synthetic personalities according to user perception

Endowing artificial conversational agents with personality is a very promising way to obtain more believable user interactions with robots and computers. However, although many authors have studied how to create an agent׳s personality and how it affects performance and user satisfaction, less attention has been paid to assess whether the designed agent׳s personality corresponds to the users׳ perception, whether it is easily recognizable, and what is the effect that the user׳s own personality has in the discrimination of the agents׳ personality. In this paper we present an assessment framework to address these issues in an integrated way, which in our opinion offers enough flexibility to consider the diversity of application domains and evaluation approaches that can be found in the literature. The framework is based on numerical measures, which facilitate the interpretation of results and makes it possible to compare and rank different agents with respect to the user׳s perception of the rendered personality. In addition, we have developed a tool that implements the framework, which may be very useful for researchers in order to easily evaluate different agent personalities.     

Techniques for Edge Stratification of Complex Graph Drawings

We propose an approach that allows a user (e.g., an analyst) to explore a layout produced by any graph drawing algorithm, in order to reduce the visual complexity and clarify its presentation. Our approach is based on stratifying the drawing into layers with desired properties; to this aim, heuristics are presented. The produced layers can be explored and combined by the user to gradually acquire details. We present a user study to test the effectiveness of our approach. Furthermore, we performed an experimental analysis on popular force-directed graph drawing algorithms, in order to evaluate what is the algorithm that produces the smallest number of layers and if there is any correlation between the number of crossings and the number of layers of a graph layout. The proposed approach is useful to explore graph layouts, as confirmed by the presented user study. Furthermore, interesting considerations arise from the experimental evaluation, in particular, our results suggest that the number of layers of a graph layout may represent a reliable measure of its visual complexity. The algorithms presented in this paper can be effectively applied to graph layouts with a few hundreds of edges and vertices. For larger drawings that contain lots of crossings, the time complexity of our algorithms grows quadratically in the number of edges and more efficient techniques need to be devised. The proposed approach takes as input a layout produced by any graph drawing algorithm, therefore it can be applied in a variety of application domains. Several research directions can be explored to extend our framework and to devise new visualization paradigms to effectively present stratified drawings.     

Epigenomes: The missing heritability in human cardiovascular disease?

Cardiovascular disease is a tremendous burden on human health and results from malfunction of various networks of biological molecules in the context of environmental stress. Despite strong evidence of heritability, many common forms of heart disease (heart failure in particular) have not yielded to genome-wide association studies to identify causative mutations acting via the disruption of individual molecules. Increasing evidence suggests, however, that genetic variation in noncoding regions is strongly linked to disease susceptibility. We hypothesize that epigenomic variation may engender different chromatin environments in the absence of (or in parallel with) changes in protein or mRNA sequence and abundance. In this manner, distinct—genetically encoded—chromatin environments can exhibit distinct responses to environmental stresses that cause heart failure, explaining a significant portion of the altered susceptibility that is observed in human disease.     

Conserved water mediated H-bonding dynamics of Ser117 and Thr119 residues in human transthyretin–thyroxin complexation: Inhibitor modeling study through docking and molecular dynamics simulation

Transthyretin (TTR) is a protein whose aggregation and deposition causes amyloid diseases in human beings. Amyloid fibril formation is prevented by binding of thyroxin (T4) or its analogs to TTR. The MD simulation study of several solvated X-ray structures of apo and holo TTR has indicated the role of a conserved water molecule and its interaction with T4 binding residues Ser117 and Thr119. Geometrical and electronic consequences of those interactions have been exploited to design a series of thyroxin analogs (Mod1–4) by modifying 5′ or 3′ or both the iodine atoms of thyroxin. Binding energy of the designed ligands has been calculated by docking the molecules in tetrameric structure of the protein. Theoretically investigated pharmacological parameters along with the binding energy data indicate the potentiality of 3′,5′-diacetyl-3,5-dichloro-l-thyronine (Mod4) to act as a better inhibitor for TTR-related amyloid diseases.     

Retracted: Critical Human Factor Evaluation of Knowledge Sharing Intention in Taiwanese Enterprises

Knowledge management (KM) is important in the Taiwan business world. Only 0.1% of SMEs, however, have been guided by the Small and Medium Enterprise Administration (SMEA) to introduce knowledge management from 1993 through 2008. The population of KM‐implementing SMEs is low. The climate of knowledge sharing has been recognized as the critical factor to successful KM. According to the research results obtained in this study, relation‐based motivation is positively related to one's intention to share knowledge. Individual workers can have increased relation‐based motivation to become leaders of SMEs building the culture of interpersonal trust and offering group‐based reward mechanisms in an organization. This research can help business managers to identify the motivational elements that can encourage investment and propose pragmatic suggestions for introducing initiatives to reinvigorate the number of SMEs implementing KM in Taiwan. © 2012 Wiley Periodicals, Inc.     

Analysis of smartphone user mobility traces for opportunistic data collection in wireless sensor networks

The increasing ubiquity of smartphones coupled with the mobility of their users will allow the use of smartphones to enhance the operation of wireless sensor networks. In addition to accessing data from a wireless sensor network for personal use, and the generation of data through participatory sensing, we propose the use of smartphones to collect data from sensor nodes opportunistically. For this to be feasible, the mobility patterns of smartphone users must support opportunistic use. We analyze the dataset from the Mobile Data Challenge by Nokia, and we identify the significant patterns, including strong spatial and temporal localities. These patterns should be exploited when designing protocols and algorithms, and their existence supports the proposal for opportunistic data collection through smartphones.