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Fog collection presents a promising solution to water scarcity in arid regions. Typically, hydrophilic surfaces are used for this purpose. This study demonstrates that electrically conductive PTFE-coated superhydrophobic carbon papers are highly effective for electrostatic fog collection. The wettability of the carbon paper has minimal impact on collection efficiency. Despite the superhydrophobic nature of the carbon papers causing condensed fog particles to aggregate into spherical droplets, this aggregation has little effect on collection performance. Additionally, the efficiency of fog collection is independent of charge type; both negative and positive high voltages yield similar results. The fog collection efficiency is directly correlated with electrostatic air current, though the relationship is nonlinear: efficiency initially increases sharply with current before leveling off.

By introducing the definition of propensity categories of relations, the implicit information in the knowledge graph is mined and the MCBE (Maximum Clique Based Expansion) algorithm is used for data expansion. Experimental results show that with baseline models TransE, RotatE, HAKE and Complex on FB15K dataset, its MRR and Hits@1 metrics are improved by (7.9%, 9.6%), (4.2%, 3.3%), (2.7%, 4.8%) and (1.7%, 2.4%), respectively. Experiments are also conducted on the FB15K, YAGO3-10, NELL-995 and DBpedia50 datasets using the TransE model as a baseline, and its MRR and Hits@1 metrics are improved on the above datasets by (7.9%, 9.6%), (0.3%, 27.7%), (20.1%, 100%), (4%, 38.7%), respectively. Finally, the MCBE algorithm is applied to the self-constructed knowledge graph of “anti-drug law” and its MRR and Hits@1 metrics are improved by (10.6%, 12.3%). The experimental results show that MCBE algorithm improves the prediction accuracy of legal knowledge graph.

Word segmentation is an important support of semantic analysis, Machine Translation, QA, knowledge mapping research work, mainly used in information retrieval, text processing, data processing and many other areas of Natural Language Processing. Therefore, the realization of word segmentation is a very meaningful work. The method of this paper is to segment the syllables of the text corpus of Lao language and complete the maximal matching of syllables and dictionaries. Then match the results of the word segmentation and the error dictionary, and correct some wrong words by the error dictionary. Finally, we use regular expressions to match the corresponding word strings in segmentation results and correct the wrong words by some artificially formulated rules of the alphabet, numbers, etc. in the Lao language. It can improve the efficiency and accuracy rate of Laos Word Segmentation.

Résumé: La prime à la paternité et la pénalité à la maternité occupent une place centrale dans l'étude des écarts de revenu entre hommes et femmes. Les auteurs font appel à la méthode des moindres carrés ordinaires, à l'analyse d'un mécanisme de médiation et à une décomposition d'Oaxaca‐Blinder pour étudier l'impact de l'arrivée d'un enfant sur le revenu des travailleurs de plateformes en Chine. Ils constatent que la pénalité liée à la maternité disparaît et que la prime à la paternité se transforme en pénalité, ce qu'ils imputent à l'influence de la pression au travail et de la ségrégation professionnelle entre les genres dans l'économie des plateformes. L'arbitrage que les hommes doivent faire entre le temps et l'énergie investis dans le travail et ceux consacrés à leurs enfants occupe en effet plus de place que dans d'autres secteurs. [ABSTRACT FROM AUTHOR]

Background: Olfactory impairment in the elderly has been shown to be associated with an increased risk of cognitive decline, and oxidative stress may be involved in this process. Dietary magnesium (Mg), as an antioxidant dietary nutrient, has been reported to be associated with cognitive decline. This study aimed to explore the effect of dietary Mg intake on cognitive decline related to olfactory impairment in older adults. Methods: Data were extracted from the National Health and Nutrition Examination Survey (NHANES) database 2013-2014. Information on dietary Mg intake was obtained from 24-hour interview. Assessment of cognitive decline included four evaluation dimensions: the Consortium to Establish a Registry for Alzheimer's Disease (including immediate and delayed), an animal fluency test, and a digit symbol substitution test. Weighted univariable and multivariable linear regression models were utilized to explore the effect of Mg on cognitive decline related to olfactory impairment, using β values and 95% confidence intervals (CIs). Subgroup analyses based on gender, history of diabetes, cardiovascular disease (CVD) and depression were further assessed. Results: In total, 1,388 elderly people were included, of whom 319 (22.98%) had olfactory impairment. After adjusting for all covariates, there was an inverse relationship between high Mg intake and cognitive decline (β=-0.21, 95%CI: -0.37 to -0.04), and olfactory impairment was positively associated with cognitive decline (β=0.53, 95%CI: 0.28 to 0.77). Among the elderly with olfactory impairment, the odds of cognitive decline were reduced in the high Mg intake group (β=0.37, 95% CI: 0.04 to 0.71) compared to the low Mg intake group (β=0.67, 95%CI: 0.39 to 0.96), especially among the elderly who were female (β=0.53, 95% CI: 0.09 to 0.98), with diabetes (β=0.72, 95% CI: 0.46 to 0.99), and without CVD (β=0.33, 95% CI: 0.05 to 0.61) and depression (β=0.38, 95% CI: 0.06 to 0.70). Conclusion: Adequate dietary Mg intake may provide potential beneficial effects, improving cognitive function, among elderly patients with olfactory impairment, which should be confirmed by scale-large prospective studies. [ABSTRACT FROM AUTHOR]