Many countries are taking strict quarantine policies to prevent the rapid spread of COVID-19 (Corona Virus Disease 2019) around the world, such as city lockdown. Cities in China and Italy were locked down in the early stage of the pandemic. The present study aims to examine and compare the impact of COVID-19 lockdown on individuals’ psychological states in China and Italy. We achieved the aim by (1) sampling Weibo users (geo-location = Wuhan, China) and Twitter users (geo-location = Lombardy, Italy); (2) fetching all the users’ published posts two weeks before and after the lockdown in each region (e.g., the lockdown date of Wuhan was 23 January 2020); (3) extracting the psycholinguistic features of these posts using the Simplified Chinese and Italian version of Language Inquiry and Word Count (LIWC) dictionary; and (4) conducting Wilcoxon tests to examine the changes in the psycholinguistic characteristics of the posts before and after the lockdown in Wuhan and Lombardy, respectively. Results showed that individuals focused more on “home”, and expressed a higher level of cognitive process after a lockdown in both Wuhan and Lombardy. Meanwhile, the level of stress decreased, and the attention to leisure increased in Lombardy after the lockdown. The attention to group, religion, and emotions became more prevalent in Wuhan after the lockdown. Findings provide decision-makers timely evidence on public reactions and the impacts on psychological states in the COVID-19 context, and have implications for evidence-based mental health interventions in two countries.

The electric double layer governs the processes of all charged surfaces in aqueous solutions; however, elucidating the structure of the water molecules is challenging for even the most advanced spectroscopic techniques. Here, we present the individual Stern layer and diffuse layer OH stretching spectra at the silica/water interface in the presence of NaCl over a wide pH range using a combination of vibrational sum frequency generation spectroscopy, heterodyned second harmonic generation, and streaming potential measurements. We find that the Stern layer water molecules and diffuse layer water molecules respond differently to pH changes: unlike the diffuse layer, whose water molecules remain net-oriented in one direction, water molecules in the Stern layer flip their net orientation as the solution pH is reduced from basic to acidic. We obtain an experimental estimate of the non-Gouy−Chapman (Stern) potential contribution to the total potential drop across the insulator/electrolyte interface and discuss it in the context of dipolar, quadrupolar, and higher order potential contributions that vary with the observed changes in the net orientation of water in the Stern layer. Our findings show that a purely Gouy−Chapman (Stern) view is insufficient to accurately describe the electrical double layer of aqueous interfaces.

Introduction. Suicide has become a serious worldwide epidemic. Early detection of individual suicide risk in population is important for reducing suicide rates. Traditional methods are ineffective in identifying suicide risk in time, suggesting a need for novel techniques. This paper proposes to detect suicide risk on social media using a Chinese suicide dictionary.Methods. To build the Chinese suicide dictionary, eight researchers were recruited to select initial words from 4,653 posts published on Sina Weibo (the largest social media service provider in China) and two Chinese sentiment dictionaries (HowNet and NTUSD). Then, another three researchers were recruited to filter out irrelevant words. Finally, remaining words were further expanded using a corpus-based method. After building the Chinese suicide dictionary, we tested its performance in identifying suicide risk on Weibo. First, we made a comparison of the performance in both detecting suicidal expression in Weibo posts and evaluating individual levels of suicide risk between the dictionary-based identifications and the expert ratings. Second, to differentiate between individuals with high and non-high scores on self-rating measure of suicide risk (Suicidal Possibility Scale, SPS), we built Support Vector Machines (SVM) models on the Chinese suicide dictionary and the Simplified Chinese Linguistic Inquiry and Word Count (SCLIWC) program, respectively. After that, we made a comparison of the classification performance between two types of SVM models.Results and Discussion. Dictionary-based identifications were significantly correlated with expert ratings in terms of both detecting suicidal expression (r = 0.507) and evaluating individual suicide risk (r = 0.455). For the differentiation between individuals with high and non-high scores on SPS, the Chinese suicide dictionary (t1: F1 = 0.48; t2: F1 = 0.56) produced a more accurate identification than SCLIWC (t1: F1 = 0.41; t2: F1 = 0.48) on different observation windows.Conclusions. This paper confirms that, using social media, it is possible to implement real-time monitoring individual suicide risk in population. Results of this study may be useful to improve Chinese suicide prevention programs and may be insightful for other countries.

Abstract. If people with high risk of suicide can be identified through social media like microblog, it is possible to implement an active intervention system to save their lives. Based on this motivation, the current study administered the Suicide Probability Scale(SPS) to 1041 weibo users at Sina Weibo, which is a leading microblog service provider in China. Two NLP (Natural Language Processing) methods, the Chinese edition of Linguistic Inquiry and Word Count (LIWC) lexicon and Latent Dirichlet Allocation (LDA), are used to extract linguistic features from the Sina Weibo data. We trained predicting models by machine learning algorithm based on these two types of features, to estimate suicide probability based on linguistic features. The experiment results indicate that LDA can find topics that relate to suicide probability, and improve the performance of prediction. Our study adds value in prediction of suicidal probability of social network users with their behaviors.

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Background Abnormalities in vocal expression during a depressed episode have frequently been reported in people with depression, but less is known about if these abnormalities only exist in special situations. In addition, the impacts of irrelevant demographic variables on voice were uncontrolled in previous studies. Therefore, this study compares the vocal differences between depressed and healthy people under various situations with irrelevant variables being regarded as covariates. Methods To examine whether the vocal abnormalities in people with depression only exist in special situations, this study compared the vocal differences between healthy people and patients with unipolar depression in 12 situations (speech scenarios). Positive, negative and neutral voice expressions between depressed and healthy people were compared in four tasks. Multiple analysis of covariance (MANCOVA) was used for evaluating the main effects of variable group (depressed vs. healthy) on acoustic features. The significances of acoustic features were evaluated by both statistical significance and magnitude of effect size. Results The results of multivariate analysis of covariance showed that significant differences between the two groups were observed in all 12 speech scenarios. Although significant acoustic features were not the same in different scenarios, we found that three acoustic features (loudness, MFCC5 and MFCC7) were consistently different between people with and without depression with large effect magnitude. Conclusions Vocal differences between depressed and healthy people exist in 12 scenarios. Acoustic features including loudness, MFCC5 and MFCC7 have potentials to be indicators for identifying depression via voice analysis. These findings support that depressed people’s voices include both situation-specific and cross-situational patterns of acoustic features.

Hydatid worms, hosted by humans and animals, impose serious human health risk and cause significant livestock production loss. To better understand the disease infection status in Xinjiang, China, we investigated the disease epidemics in 4 livestock animals, i.e., cattle, sheep (both sheep and goat), camels, and horses, slaughtered at the abattoirs in Urumqi, Yining, Tacheng, and Altay areas. The results showed that the animals were infected at different rates, in the order of sheep (9.8%), cattle (8.4%), camels (6.8%), and horses (4.3%). The infection rates were found to be different between the abattoirs in various regions even for the same animals. For sheep, the rates increased significantly as the animals grew older. It was 1.9% before 1 year of age and increased to 8.2% in the age of 1-2 years, and further increased to 12.3% when the animals were 3-4 years old, and reached 17.2% when they were 5-6 year old. Sheep older than 6 years had an infection rate of 19.5%. This study demonstrates that the 4 livestock animals in the pastoral areas in Xinjiang were infected by the parasites to various extend. This study is the first systematic investigation of the hydatid worms in various livestock animals in Xinjiang, China, which provides epidemiological information about the infection of hydatid worms in livestock, and is valuable in developing strategies for prevention and control of the hydatid disease.

Socially disadvantaged rural women were disproportionately affected by schizophrenia-related disability. Limited access to health services may have contributed to the increased disease burden among rural women.