Exploring the longitudinal relationship between lockdown policy stringency and public negative emotions among 120 countries during the COVID-19 pandemic: mediating role of population mobility

Background: To limit the spread of COVID-19, governments worldwide have implemented a series of lockdown policies to restrict the social activities of people. Although scholars suggest that such policies may produce negative effects on public emotions, the existing research is limited because it only provides a cross-sectional snapshot of the effect of lockdown policies in small and local samples. Using large-scale longitudinal cross-country data, the current study aims to gain a better understanding of the dynamic effect of lockdown policies on public emotions and their underlying mechanisms. Methods: Drawing on a large-scale longitudinal data from multiple sources, the study employs fixed-effects models to analyze the association between lagged lockdown policy stringency and public negative emotions among 120 countries from February to July 2020 (N = 9,141 country-day observations). The bootstrapping mediation test is used to examine the mediation effects of increased population mobility in residential areas. Results: The results show a statistically significant and positive association between lagged lockdown policy stringency and general public negative emotion (standardized coefficient = 0.32, CI = 0.30–0.35, p < 0.001). This pattern remains similar to other specific negative emotions, such as depression, anxiety, hopelessness, and helplessness. Moreover, the negative health effects of lockdown policy stringency are significantly mediated by increased mobility in residential areas (51–74% points, p < 0.001). Conclusion: The findings confirm that stringent lockdown policies have a negative effect on public emotions via confining population mobility residential areas. To tackle the COVID-19, future public health policies should pay more attention to the unintended negative consequences of lockdown measures on public emotions

MSEC2006-21035 WELD-BEAD MOVEMENT OF MULTI-GAUGE TAILOR-WELDED BLANK DURING DRAWING SQUARE CUP WITH REVERSE-CONVEX

ABSTRACT To decrease the weight of auto panels and reinforce the safety of vehicles, the tailor-welded blank (TWB) has been used widely in the auto panels manufacturing. Basic principles and advantages of TWB are described at first. Then the technologies of numerical simulation modeling for TWB are researched. By means of numerical simulation, the weld-bead movement and formability of TWB with the same mechanical property and multi-gauges are investigated. After analyzing the weld-bead movement in three different drawing depth combinations with same total deformed depth, some conclusions of weld-bead movement are drawn finally. It reveals the relationships between the weld-bead movement and formability of multi-gauge TWB

Modeling Fine-grained Information via Knowledge-aware Hierarchical Graph for Zero-shot Entity Retrieval

Zero-shot entity retrieval, aiming to link mentions to candidate entities under the zero-shot setting, is vital for many tasks in Natural Language Processing. Most existing methods represent mentions/entities via the sentence embeddings of corresponding context from the Pre-trained Language Model. However, we argue that such coarse-grained sentence embeddings can not fully model the mentions/entities, especially when the attention scores towards mentions/entities are relatively low. In this work, we propose GER, a \textbf{G}raph enhanced \textbf{E}ntity \textbf{R}etrieval framework, to capture more fine-grained information as complementary to sentence embeddings. We extract the knowledge units from the corresponding context and then construct a mention/entity centralized graph. Hence, we can learn the fine-grained information about mention/entity by aggregating information from these knowledge units. To avoid the graph information bottleneck for the central mention/entity node, we construct a hierarchical graph and design a novel Hierarchical Graph Attention Network~(HGAN). Experimental results on popular benchmarks demonstrate that our proposed GER framework performs better than previous state-of-the-art models. The code has been available at https://github.com/wutaiqiang/GER-WSDM2023.Comment: 9 pages, 5 figure

Contact force sensor based on microfiber Bragg grating

We demonstrate a miniature contact force sensor based on a 30-µm diameter microfiber Bragg grating packaged with a conforming elastomer material features extremely high sensitivity up to 0.8-mN to contract force.Department of Electrical EngineeringDepartment of Electronic and Information Engineerin

OPO-CVI: design and implementation of an ocean profiling observation system for wave-powered vertical profiler following an ISO standard

This paper presents the design and implementation of an ISO-compliant ocean profiling observation system for wave-powered vertical profiler. This system aims to provide a comprehensive, scalable, and interoperable solution for high-resolution, real-time oceanic observation. As a part of this system, we introduce a wave-powered vertical profiler, known as “Wave Master,” designed to offer enhanced stability and reliability for long-term oceanic data collection. The core of the paper focuses on the Ocean Profiling Observation Complex Virtual Instrument (OPO-CVI), a comprehensive system developed in alignment with ISO 21851 standard. OPO-CVI seamlessly integrates data collection, transmission, storage, and visualization. Specifically, OPO-CVI addresses the challenges of information isolation, system rigidity, and lack of modularity in traditional ocean profiling methods by standardizing data formats and transmission protocols, allowing for seamless integration of new observation elements, and employing a modular architecture for enhanced scalability and reusability. By offering detailed technical insights into the OPO-CVI architecture and its compliance with ISO 21851 standard, this paper aims to contribute significantly to the advancement of standardized, efficient, and reliable oceanic observation systems

Amplified role of potential HONO sources in O3 formation in North China Plain during autumn haze aggravating processes

Co-occurrences of high concentrations of PM2.5 and ozone (O-3) have been frequently observed in haze-aggravating processes in the North China Plain (NCP) over the past few years. Higher O-3 concentrations on hazy days were hypothesized to be related to nitrous acid (HONO), but the key sources of HONO enhancing O-3 during haze-aggravating processes remain unclear. We added six potential HONO sources, i.e., four groundbased (traffic, soil, and indoor emissions, and the NO2 heterogeneous reaction on ground surface (Het(ground))) sources, and two aerosol-related (the NO2 heterogeneous reaction on aerosol surfaces (Het(aerosol)) and nitrate photolysis (Phot(nitrate))) sources into the WRF-Chem model and designed 23 simulation scenarios to explore the unclear key sources. The results indicate that ground-based HONO sources producing HONO enhancements showed a rapid decrease with height, while the NO C OH reaction and aerosol-related HONO sources decreased slowly with height. Photnitrate contributions to HONO concentrations were enhanced with aggravated pollution levels. The enhancement of HONO due to Phot(nitrate) on hazy days was about 10 times greater than on clean days and Phot(nitrate) dominated daytime HONO sources (similar to 30 %-70% when the ratio of the photolysis frequency of nitrate (J(nitrate)) to gas nitric acid (JHNO(3)) equals 30) at higher layers (>800 m). Compared with that on clean days, the Phot(nitrate) contribution to the enhanced daily maximum 8 h averaged (DMA8) O-3 was increased by over 1 magnitude during the haze-aggravating process. Phot(nitrate) contributed only similar to 5% of the surface HONO in the daytime with a J(nitrate) =JHNO(3) ratio of 30 but contributed similar to 30 %-50% of the enhanced O-3 near the surface in NCP on hazy days. Surface O-3 was dominated by volatile organic compound-sensitive chemistry, while O-3 at higher altitudes ( >800 m) was dominated by NOx-sensitive chemistry. Phot(nitrate) had a limited impact on nitrate concentrations (Peer reviewe

TencentPretrain: A Scalable and Flexible Toolkit for Pre-training Models of Different Modalities

Recently, the success of pre-training in text domain has been fully extended to vision, audio, and cross-modal scenarios. The proposed pre-training models of different modalities are showing a rising trend of homogeneity in their model structures, which brings the opportunity to implement different pre-training models within a uniform framework. In this paper, we present TencentPretrain, a toolkit supporting pre-training models of different modalities. The core feature of TencentPretrain is the modular design. The toolkit uniformly divides pre-training models into 5 components: embedding, encoder, target embedding, decoder, and target. As almost all of common modules are provided in each component, users can choose the desired modules from different components to build a complete pre-training model. The modular design enables users to efficiently reproduce existing pre-training models or build brand-new one. We test the toolkit on text, vision, and audio benchmarks and show that it can match the performance of the original implementations