Photocatalysis in a novel semiconducting optical fiber monolithic reactor for wastewater treatment

The development of photocatalytic reactors is essential for the successful exploitation of heterogeneous photocatalysis on semiconductor particles, which has been shown to be an effective means of removing organic pollutants from wastewater streams. In this dissertation, a novel photocatalytic optical fiber monolith reactor (OFMR), which employed a ceramic multi-channel monolith as a support for TiO2 and quartz fibers inserted inside the monolithic channels as both a light-transmitting conductor and a support for TiO2, was developed for wastewater treatment by investigating the photocatalytic degradation of o-dichlorobenzene (DCB) and phenanthrene (PHE). This configuration provides a high surface area for catalyst coating per unit reactor volume, reduces the mass transport limitations, and allows for high throughput at low pressure drop. Using optical fiber to deliver UV light can remotely control the reactor. The effects of water flow velocity, initial contaminant concentration, thickness of the TiO2 film on the optical fiber and incident UV light intensity were investigated and optimized. The results showed mass transfer effects could not be ignored due to the relatively low flow Reynolds number. Optimum thickness of TiO2 film on the optical fiber was found to be close to 0.4 µm in this study. The kinetics of DCB and PHE degradation were pseudo-first order. Greater apparent quantum efficiency was observed for the OFMR compared with that of the continuous annular reactor, which suggested that this novel reactor has the potential in photocatalytic applications. The light distribution profile inside each cell of the monolith was quantitatively analyzed. The radiation field model with the fitting parameters was set up and validated. The two-dimensional heterogeneous convective-diffusion-reaction steady-state model of a multi-channel OFMR was developed by incorporating an empirical radiation field sub-model, an annular flow dynamics model and a Langmuir-Hinshelwood kinetics sub-model. Reasonable agreement was found between the model-predicted and experimentally observed photodegradation conversion data within the limits of experimental error, using the total rate constant as the only adjustable parameter. The model can be used to optimize the design parameters in an OFMR

EMIR: A novel emotion-based music retrieval system

Music is inherently expressive of emotion meaning and affects the mood of people. In this paper, we present a novel EMIR (Emotional Music Information Retrieval) System that uses latent emotion elements both in music and non-descriptive queries (NDQs) to detect implicit emotional association between users and music to enhance Music Information Retrieval (MIR). We try to understand the latent emotional intent of queries via machine learning for emotion classification and compare the performance of emotion detection approaches on different feature sets. For this purpose, we extract music emotion features from lyrics and social tags crawled from the Internet, label some for training and model them in high-dimensional emotion space and recognize latent emotion of users by query emotion analysis. The similarity between queries and music is computed by verified BM25 model

How head posture affects perceived cooperativeness : a cross-cultural perspective

This research was supported by grants from the National Natural Science Foundation of China (No. 62076051).Previous research has tested whether culture moderates the relationship between head tilt and perceptions of a cooperation-relevant construct. In this paper, we replicated the effects of head posture on perceived traits and compared Chinese and American participants to explore whether difference in cultural background (collectivist and individualist) affects perceptual attribution. Specifically, we investigated how head posture (level, up or down) affects perceptions of cooperativeness. In Experiment 1, Chinese and American participants rated Asian and Caucasian faces in three postures for perceived cooperativeness on a seven-point Likert scale. In Experiment 2, participants ranked the cooperativeness of the three postures of the same faces. In Experiment 3, participants scrolled through face images and manually manipulated vertical head angle to maximise apparent cooperativeness. We found that for both Chinese and American participants a neutral head level posture was perceived as more cooperative than head up and down postures. The optimal head posture for maximised apparent cooperativeness was close to level but with a slight downward rotation. While there was cross-cultural consistency in perceptions, Chinese participants exhibited greater sensitivity to postural cues in their judgments of cooperation compared to American participants. Our results suggest a profound effect of posture on the perception of cooperativeness that is common across cultures and that there are additional subtle cross-cultural differences in the cues to cooperativeness.Publisher PDFPeer reviewe

Apparent emotional expression explains the effects of head posture on perceived trustworthiness and dominance, but a measure of facial width does not

This research was supported by grants from the National Natural Science Foundation of China (No. 61602079; No.61632011) and the Humanity and Social Science Youth Foundation of Ministry of Education of China (No. 16YJCZH141).Interpreting the personality and the disposition of people is important for social interaction. Both emotional expression and facial width are known to affect personality perception. Moreover, both the apparent emotional expression and the apparent width-to-height ratio of the face change with head tilt. We investigated how head tilt affects judgements of trustworthiness and dominance and whether such trait judgements reflect apparent emotion or facial width. Sixty-seven participants rated the dominance, emotion, and trustworthiness of 24 faces posing with different head tilts while maintaining eye gaze at the camera. Both the 30° up and 20° down head postures were perceived as less trustworthy and more dominant (less submissive) than the head-level posture. Change in perceived trustworthiness and submissiveness with head tilt correlated with change in apparent emotional positivity but not change in facial width. Hence, our analysis suggests that apparent emotional expression provides a better explanation of perceived trustworthiness and dominance compared with cues to facial structure.PostprintPeer reviewe

The Mechanism of Theory-based HIV Behavioral Intervention on Condom Use among Rural-to-urban Migrants in China: The Mediating Roles of HIV Knowledge and Condom Use Self-efficacy

Previous studies have suggested HIV knowledge and self-efficacy are important cognitive factors that might influence condom use behaviors. However, data were limited regarding their mediating effects on condom use during behavioral interventions. This study examined the mechanistic roles of these two factors on the effect of a community-based intervention aiming to increase condom use behaviors and intention among young rural-to-urban migrants in China. Data were derived from a community-based HIV behavioral intervention trial among 639 young sexually active rural-to-urban migrants in Beijing, China. Path analyses were used to examine the direct and indirect effects of the intervention program on condom use behaviors and intention over a 12-month follow-up. HIV knowledge and condom use self-efficacy at 6-month follow-up served as mediators in models. Path analyses revealed that intervention program increased condom use behaviors at 12 months through the increase of HIV knowledge at 6 months. Likewise, the intervention program increased condom use intention through the increases of HIV knowledge and condom use self-efficacy. The results suggested HIV knowledge played an important mediating role on the effect of the intervention program on condom use behaviors and intention. Additionally, condom use self-efficacy played an important role in increasing condom use intention. To increase condom use behaviors and intention among migrants, future studies are warranted that focus on improving HIV knowledge and helping migrants overcome cognitive barriers of condom use. Other efforts targeting structural and environmental barriers, such as limited healthcare access due to household registration status, are also needed to increase HIV protective behaviors

An Identity Perspective on Online Healthcare Communities

Online healthcare communities often experience high churn rates. Our study investigates this phenomenon by integrating the concepts of social stigma, psychological capital, and social identity. Based on survey data from an online community serving lymphoma patients, we found that 1) users’ positive social identity increased their participation and recommendation intentions through enhanced psychological capital empowered by the online community; 2) stigmatized social identity hampered participation and recommendation intentions through decreased psychological capital; 3) users’ personal identity moderated the mediated impacts of positive and stigmatized social identities on participation and recommendation intentions through psychological capital, and 4) participation intention positively influenced recommendation intention. Our study applied the identity theory with a novel approach and offered insights on the development and management of online healthcare communities for both researchers and practitioners

Bi-Preference Learning Heterogeneous Hypergraph Networks for Session-based Recommendation

Session-based recommendation intends to predict next purchased items based on anonymous behavior sequences. Numerous economic studies have revealed that item price is a key factor influencing user purchase decisions. Unfortunately, existing methods for session-based recommendation only aim at capturing user interest preference, while ignoring user price preference. Actually, there are primarily two challenges preventing us from accessing price preference. Firstly, the price preference is highly associated to various item features (i.e., category and brand), which asks us to mine price preference from heterogeneous information. Secondly, price preference and interest preference are interdependent and collectively determine user choice, necessitating that we jointly consider both price and interest preference for intent modeling. To handle above challenges, we propose a novel approach Bi-Preference Learning Heterogeneous Hypergraph Networks (BiPNet) for session-based recommendation. Specifically, the customized heterogeneous hypergraph networks with a triple-level convolution are devised to capture user price and interest preference from heterogeneous features of items. Besides, we develop a Bi-Preference Learning schema to explore mutual relations between price and interest preference and collectively learn these two preferences under the multi-task learning architecture. Extensive experiments on multiple public datasets confirm the superiority of BiPNet over competitive baselines. Additional research also supports the notion that the price is crucial for the task.Comment: This paper has been accepted by ACM TOI