Understanding User Engagement in Online Communities during COVID-19 Pandemic: Evidence from Sentiment and Semantic Analysis on YouTube

Since the outbreak of COVID-19, the pandemic has changed the lives of many people and brought dramatic motional experiences. Among many social media platforms, YouTube saw the most significant growth of any social media app among American users during the pandemic, according to the Pew Research Center on 7th April 2021. Exposure to COVID-19 related news can have a significant impact on user engagement on social networks. Different news may trigger different emotions (i.e., anger, anticipation, disgust, fear, joy, sadness, surprise, or trust), and a user may engage differently in response to the news. On YouTube, user engagement is manifested through actions such as liking, disliking, commenting, or sharing videos. During the pandemic, many users provide constructive comments that are encouraging, respectful, and informative to support each other. We applied sentiment analysis in the study to investigate different emotions and applied semantic analysis to investigate positive appraisal (i.e., encouraging, respectful, and informative) to identify salient factors that can motivate user engagement. The findings of the work shed light on how social network platforms could encourage constructive comments to help people provide emotional support to each other during pandemics through using positive appraisal in online news comments. The first research objective is to study the impact of sentiment valence of different emotions on people’s liking of news comments. News about COVID-19 on social networks may provide valuable information but also bring about public panic. In response to this COVID-19 related news, reviewers expressed their feelings by clicking the like, dislike buttons to the video and comments, or writing some comments under the video on YouTube. Some positive news was followed by comments expressing their anticipation, joy, and trust, while negative news might trigger sadness, fear, disgust, or anger. Our research focuses on sentiment analysis of news titles and the comments following each video. News title provides important information about the video, showing the summary of the video and allowing people to get a first glimpse of the content of the video. Through sentiment analysis of title and comments, correlations could be found between title/comments sentiment and user engagement. The second research objective is to investigate the impact of comments’ positive appraisal (i.e., encouraging, respectful, and informative content) on user engagement. The informative comments under the negative news have significant implications for the audience. They can be considered as a complement or judgment of the video content. Encouraging and respectful comments also help people build good conversations online. Our research focuses on semantic analysis of news titles and comments based on the three dimensions of positive appraisal and analyzes their impacts on user engagement to like the corresponding comment. We discuss the correlation between video title sentiment and the positive appraisal followed in the comments of the video to provide good conversations on the platform. A group of 38,085 online comments was collected from more than 400 different publishers from January 1st to January 30th, 2021, on YouTube. The dataset contains the most-viewed videos that were related to at least one of the following search queries: coronavirus, COVID-19, pandemic, or vaccine. NRC lexicon is adopted in the sentiment analysis to identify different emotions in titles and comments of the video. We adopt the topic modeling method and build a classifier from the Yahoo News Annotated Comments Corpus to identify constructive online comments for specific topics. We also measure inter-annotator agreements and compare the reliability of manual annotation and the classifier. We find that longer titles and sad emotions can obtain more likes on the comments of COVID-19 related news. During the pandemic, people tend to show their support when they find others are quite sad. We also expect to see correlations between some positive appraisals and user engagement

Model and Frequency Control for Three-Phase Wireless Power Transfer System

In order to the eliminate the “dead spot” in the traditional three-phase wireless power transfer (WPT) system, a three-phase WPT system with an asymmetric magnetic circuit is presented in this paper. Additionally, mathematical model of the system is established and the system parameters are optimized. Based on the fact that the resonant frequency and efficiency are greatly varied with the load, a method based on impedance conversion is further proposed to improve the frequency stability and system efficiency. Finally, simulation and experimental results show that the proposed method is reliable and feasible to eliminate the “dead spot.

Honor, Goal Setting, and Energy Conservation: Evidence from a Field Experiment in Student Dormitories

Non-monetary incentives are increasingly being studied in encouraging energy conservation. In light of this, we conducted a natural field experiment in student dormitories to assess the effect of honor-based incentives and goal setting on electricity saving and the intrinsic motivation to save energy. Using a difference-in-difference model, we found that goal setting reduced the dormitories' electricity consumption by 15.93\% on average compared to the control group. However, the honor-based incentives were not effective on average. In addition, the study found that both honor-based incentives and goal setting, on average, did not crowd out or crowd in the intrinsic motivation to save electricity in dormitories. The heterogeneity analysis showed that the more the dormitory values honor incentives, the more its intrinsic motivation was crowded in by honor incentives. We also found dormitory characteristics affect the crowding effect on the intrinsic motivation

Corrosion resistance of crystalline and amorphous CuZr alloys in NaCl aqueous environment and effect of corrosion inhibitors

CuZr alloys are the basis of a family of metallic glasses with large glass forming ability and remarkable mechanical properties. The corrosion response of prepared crystalline and amorphous CuxZr100-x alloys (x = 40, 50, 64 at%), as well as bare Cu and Zr, in a severe corrosive environment, was tested. The alloys were immersed in 3 wt% NaCl aqueous solution. With the aim to increase the resistance of copper as less corrosion alloy component, nine imidazole-based compounds with different functional groups were tested as potential corrosion inhibitors. Potentiodynamic polarization measurements, electrochemical impedance spectroscopy, and long-term immersion tests followed by X-ray photoelectron spectroscopy and microscopy analysis were carried out. Overall, all the tested amorphous alloys exhibit a much better corrosion resistance than their crystalline counterparts in the presence and absence of inhibitors. The main factor controlling the corrosion resistance of the alloys appears to be the Zr-rich (or at least equiatomic) amorphous structure, the effect of the inhibitors being secondary. Results therefore show a complex relationship between inhibitor performance, microstructure and composition of CuZr alloys.Peer ReviewedPostprint (published version

Enhanced photoproduction of hydrogen on Pd/TiO2 prepared by mechanochemistry

Supported metal clusters are considered as promising cocatalysts in heterogeneous photocatalysis due to their singular geometric structures and unique reactivity. Nevertheless, to explore efficient synthetic routes that result in stable supported clusters with tailored active sites is an urgent yet challenging task. Here, a photocatalyst with highly dispersed Pd clusters onto TiO2 is synthesized through only one-step ball milling procedure. The obtained Pd clusters form a particular metal-support interface, which has the ability to rearrange the small clusters evolving into Pd nanoparticles during the photocatalytic H2 production process, and maintain a stable photocatalytic performance up to 100 h of continuous operation. Moreover, the unique interaction between Pd clusters and titania support was only observed in the ball-milled sample, and it disappeared after a calcination treatment. The mechanochemical strategy paves the way to stabilize supported metal clusters onto semiconductors without any organic compounds involved.Postprint (published version

DAMO-StreamNet: Optimizing Streaming Perception in Autonomous Driving

Real-time perception, or streaming perception, is a crucial aspect of autonomous driving that has yet to be thoroughly explored in existing research. To address this gap, we present DAMO-StreamNet, an optimized framework that combines recent advances from the YOLO series with a comprehensive analysis of spatial and temporal perception mechanisms, delivering a cutting-edge solution. The key innovations of DAMO-StreamNet are: (1) A robust neck structure incorporating deformable convolution, enhancing the receptive field and feature alignment capabilities. (2) A dual-branch structure that integrates short-path semantic features and long-path temporal features, improving motion state prediction accuracy. (3) Logits-level distillation for efficient optimization, aligning the logits of teacher and student networks in semantic space. (4) A real-time forecasting mechanism that updates support frame features with the current frame, ensuring seamless streaming perception during inference. Our experiments demonstrate that DAMO-StreamNet surpasses existing state-of-the-art methods, achieving 37.8% (normal size (600, 960)) and 43.3% (large size (1200, 1920)) sAP without using extra data. This work not only sets a new benchmark for real-time perception but also provides valuable insights for future research. Additionally, DAMO-StreamNet can be applied to various autonomous systems, such as drones and robots, paving the way for real-time perception. The code is available at https://github.com/zhiqic/DAMO-StreamNet

Determining the Optimal N Input to Improve Grain Yield and Quality in Winter Wheat With Reduced Apparent N Loss in the North China Plain

Excessive or improper nitrogen (N) application rates negatively affect crop production and thereby environmental quality, particularly for winter wheat production in the North China Plain. Therefore, it is very important to optimize N fertilizer input to balance grain yield, environmental risk, and benefits under irrigated conditions. Three long-term stationary field experiments including five N levels, from 0 to 300 kg ha-1 [0 (N0), 90 (N90), 180 (N180), 240 (N240), and 300 (N300) kg ha-1] were carried out to investigate the effects of N regime on wheat yield, photosynthesis, and N balance at different sites. The grain yield and protein content increased quadratically with N rate, and the maximum values were 8087 kg ha-1 and 13.9% at N application rates of 250 and 337 kg N ha-1, respectively. N application increased the photosynthetic fluorescence parameters (Pn, Gs, and Tr) and N metabolism enzyme activities (NR and GS) which then increased grain yield. The leaching of soil nitrate into the deeper soil layers ( > 100 cm) increased with higher N fertilization and experimental years. The partial factor productivity (PFPN) was decreased by N because the apparent N loss increased with N application rate. In order to balance grain yield, N use efficiency (NUE), and N loss, the recommended N rate should be 120–171 kg N ha-1, and the corresponding yields and apparent N loss were 7278–7787 ka ha-1 and 22–37 kg ha-1, respectively