Crowdsourcing Argumentation Structures in Chinese Hotel Reviews

Argumentation mining aims at automatically extracting the premises-claim discourse structures in natural language texts. There is a great demand for argumentation corpora for customer reviews. However, due to the controversial nature of the argumentation annotation task, there exist very few large-scale argumentation corpora for customer reviews. In this work, we novelly use the crowdsourcing technique to collect argumentation annotations in Chinese hotel reviews. As the first Chinese argumentation dataset, our corpus includes 4814 argument component annotations and 411 argument relation annotations, and its annotations qualities are comparable to some widely used argumentation corpora in other languages.Comment: 6 pages,3 figures,This article has been submitted to "The 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC2017)

Learning Verb-Noun Collocations Through Multiple-Choice Exercises: Do Distractors Benefit or Hinder Later Recall?

This study aimed to investigate under what conditions multiple-choice exercises benefit second language learners’ acquisition of lexical phrases. Of particular interest was the question whether the distractors in the multiple-choice items create interference when learners’ later try to recall the lexical phrases. Twenty advanced ESL (English as a Second Language) learners were given 20 multiple-choice items on verb-noun collocations (e.g., run a business, take a toll, speak volumes) followed by feedback. They were then tested on the same collocations two weeks later by means of gap-fill items. The participants were invited to verbalize their thoughts during the exercise and the test. They were subsequently shown the multiple-choice exercise again and asked if they could remember how they had responded to each item and what the correct response option was. This mixed-methods study revealed poor effectiveness of the multiple-choice exercises overall. When learners failed to produce the correct response in the post-test, this was either because they could not remember which of the response options in the multiple-choice item turned out to be the correct one or because they simply had not recollection of the exercise item. The likelihood of producing a correct response in the post-test increased when learners (a) chose the correct response option in the multiple-choice item, (b) remembered the multiple-choice item, and (c) accurately recalled the feedback received on the item. Individual learner differences and item characteristics also influenced the effectiveness of multiple-choice exercises for learning collocations. The findings suggest that, for multiple-choice exercises to be relatively beneficial for collocation learning, they need to be designed and implemented in a way that ensures a high accuracy rate at the exercise stage

Effect of dry-heating with pectin on gelatinization properties of sweet potato starch

Purpose: To evaluate the effect of dry-heating with pectin at different dry heating temperatures, heating times and pH on the gelatinization properties of sweet potato starch.Methods: The gelatinization properties of sweet potato starch - pectin blend were analyzed using a rapid viscosity analyzer (RVA), differential scanning calorimeter (DSC), and gel texture analyzer (TPA).Results: The viscosity of the blends of sweet potato starches and pectin increased initially, and then decreased. Viscosity was highest at 120 °C, with a value of 744 cp. High viscosity values were also obtained after dry-heating for 2 and 7 h (540 cp and 639 cp, respectively). The enthalpy of the blend declined with increasing heat-treatment temperature from 3.973 J/g at 0 °C to 3.021 J/g at 150 °C. The initial (T0), peak (Tp), and terminal (Tc) gelatinization temperatures of the blends were all lower than corresponding values at 0 °C. Gelatinization enthalpy values gradually increased with increase in dryheating time and pH although they were still lower than for the control samples. In addition, as T0, Tp, and Tc values of the blend increased, the gelatinization temperature range became narrower. The hardness and viscosity of the blends increased initially, and then decreased after the dry-heat treatment. The hardness of treated samples was higher than that of control, and peaked at 130 °C, 4 h, and pH 11. The resilience of the blends attained a peak value after 2 h of dry-heat treatment at 120 °C and pH 9.Conclusion: The results show that dry-heating with pectin is an effective way of improving the gelatinization and gel properties of sweet potato starch. This finding is considered significant for the developing of new modified starch from sweet potatoes.Keywords: Sweet potato starch, Pectin, Dry heat, Gelatinization, Viscosity, Hardness, Enthalp

Effect of steam explosion pre-treatment on molecular structure of sweet potato starch

Purpose: To examine the effect of steam-explosion (SE) strength on the molecular structure of sweet potato starch.Methods: Sweet potato starch was pre-treated using SE method. The effects of SE pressure and pressure-holding time on the molecular structure of the sweet potato starch were investigated by gel chromatography (GPC), infrared spectroscopy, and grading analysis.Results: The molecular weight (MW) of the starch pre-treated by SE technology decreased with increasing explosion pressure and pressure-holding time; however, the individual MW of amylopectin and amylose declined from 439,834 and 6578 to 238,603 and 4845, respectively. Furthermore, the peak area ratio (obtained by GPC) of amylopectin decreased from 84.39 to 65.16 % while that of amylose increased from 15.61 to 34.84 %. No new absorption peaks were found in the infrared spectra of sweet potato starch following SE pre-treatment. Crystallization index and median diameter of sweet potato starch increased from 1.661 to 1.959 and from 13.73 μm to 76.36 μm, respectively, with rising pressure and pressure-holding time, following SE pre-treatment.Conclusion: SE pre-treatment effectively degrades the degree of polymerisation of molecular chains in sweet potato starch and enhances the degree of crystallinity thereof. SE method is an approach for the production of sweet potato starch with high-level anti-digestion characteristics.Keywords: Sweet potato starch, Steam-explosion, Molecular weight, Degree of crystallinity, Particle diamete

A curve model for association of serum homocysteine with carotid artery hemodynamics

Purpose: To investigate the correlation between carotid artery hemodynamics and serum homocysteine.Methods: A total of 894 participants made up of 439 male (49.11 %) and 455 female (50.89 %) from Ma’anshan, China, enrolled in the cross-sectional study. Data collection included demographics, blood sample and carotid ultrasonography. Piecewise linear regression analysis was used to analyze the relationship between serum homocysteine and carotid artery hemodynamics.Results: Homocysteine (Hcy) levels were divided into four groups by quartiles. The populations of the groups were 226, 220, 222, 226; and their mean ages were 56.52 ± 10.49, 62.27 ± 10.06, 63.42 ± 9.81 and 65.38 ± 10.56 years, respectively. After adjustment for blood biochemical and demographics factors, U-shaped and S-shaped curves were as observed between Hcy and carotid artery hemodynamics. The adjusted regression analysis showed that the threshold values of Hcy with end diastolic velocity (EDV) of right common carotid artery (CCA) were 12.50 and 19.00, while for the EDV of right internal carotid artery (ICA), the values were 11.50 and 22.00. U-shaped curves were observed between Hcy and peak systolic velocity (PSV) of left CCA, EDV of left CCA, PSV of left ICA and EDV of left ICA. The threshold values of Hcy with PSV of left CCA, EDV of left CCA, PSV of left ICA and EDV of left ICA were 14.00, 14.00, 14.00 and 13.50, respectively.Conclusion: These results indicate that a significant correlation exists between homocysteine at different concentrations and carotid artery hemodynamics.Keywords: Homocysteine, Hemodynamics, End diastolic velocity, Peak systolic velocit

Integrative single-cell transcriptomic investigation unveils long non-coding RNAs associated with localized cellular inflammation in psoriasis

Psoriasis is a complex, chronic autoimmune disorder predominantly affecting the skin. Accumulating evidence underscores the critical role of localized cellular inflammation in the development and persistence of psoriatic skin lesions, involving cell types such as keratinocytes, mesenchymal cells, and Schwann cells. However, the underlying mechanisms remain largely unexplored. Long non-coding RNAs (lncRNAs), known to regulate gene expression across various cellular processes, have been particularly implicated in immune regulation. We utilized our neural-network learning pipeline to integrate 106,675 cells from healthy human skin and 79,887 cells from psoriatic human skin. This formed the most extensive cell transcriptomic atlas of human psoriatic skin to date. The robustness of our reclassified cell-types, representing full-layer zonation in human skin, was affirmed through neural-network learning-based cross-validation. We then developed a publicly available website to present this integrated dataset. We carried out analysis for differentially expressed lncRNAs, co-regulated gene patterns, and GO-bioprocess enrichment, enabling us to pinpoint lncRNAs that modulate localized cellular inflammation in psoriasis at the single-cell level. Subsequent experimental validation with skin cell lines and primary cells from psoriatic skin confirmed these lncRNAs’ functional role in localized cellular inflammation. Our study provides a comprehensive cell transcriptomic atlas of full-layer human skin in both healthy and psoriatic conditions, unveiling a new regulatory mechanism that governs localized cellular inflammation in psoriasis and highlights the therapeutic potential of lncRNAs in this disease’s management

Analysis for sources of atmospheric α- and γ-HCH in gas and particle-associated phase in Dalian, China by multiple regression

Atmospheric concentrations of α- and γ-hexachlorocyclohexanes were measured once a week in Dalian throughout 2008, using a high-volume air sampler, to estimate diurnal, monthly and seasonal variations. Multiple regression analysis was used to estimate the impact of selected meteorological conditions on atmospheric concentrations of hexachlorocyclohexanes and to identify the potential source regions. Overall, α- and γ-hexachlorocyclohexanes were mainly associated with the gas phase, with an annual mean gas-phase concentration of 36±30 and 10±9.8pgm-3 respectively. On the other hand, mean particle (PM10) associated concentrations throughout the year were 1.9±2.4 and 0.46±0.43pgm-3 respectively. Gas-phase concentration of α- and γ-hexachlorocyclohexanes peaked in the autumn season whereas highest concentrations in the particle phase were measured in spring. Ratio of α-/γ-isomer ranged from 3.7 to 7.4 in the gas phase which was close to the ratio in technical hexachlorocyclohexanes (5-7). In the particle-associated phase this ratio ranged from 1.2 to 3.8, with the exception of daytime samples in spring (up to 16) and summer seasons (up to 14) and this exception could be due to the isomerization from γ- to α- in ambient air, at least partly resulted from the impact of sunlight. Regression analysis showed that, at the sampling site, concentrations of α- and γ-hexachlorocyclohexanes in the gas phase were both elevated with increasing temperature and wind speed, whereas in the particle-associated phase their concentrations tended to remain stable