Activity-aware Human Mobility Prediction with Hierarchical Graph Attention Recurrent Network

Human mobility prediction is a fundamental task essential for various applications, including urban planning, location-based services and intelligent transportation systems. Existing methods often ignore activity information crucial for reasoning human preferences and routines, or adopt a simplified representation of the dependencies between time, activities and locations. To address these issues, we present Hierarchical Graph Attention Recurrent Network (HGARN) for human mobility prediction. Specifically, we construct a hierarchical graph based on all users' history mobility records and employ a Hierarchical Graph Attention Module to capture complex time-activity-location dependencies. This way, HGARN can learn representations with rich human travel semantics to model user preferences at the global level. We also propose a model-agnostic history-enhanced confidence (MAHEC) label to focus our model on each user's individual-level preferences. Finally, we introduce a Temporal Module, which employs recurrent structures to jointly predict users' next activities (as an auxiliary task) and their associated locations. By leveraging the predicted future user activity features through a hierarchical and residual design, the accuracy of the location predictions can be further enhanced. For model evaluation, we test the performances of our HGARN against existing SOTAs in both the recurring and explorative settings. The recurring setting focuses on assessing models' capabilities to capture users' individual-level preferences, while the results in the explorative setting tend to reflect the power of different models to learn users' global-level preferences. Overall, our model outperforms other baselines significantly in all settings based on two real-world human mobility data benchmarks. Source codes of HGARN are available at https://github.com/YihongT/HGARN.Comment: 11 page

Research and Prediction on the Sharing of WeChat Official Accounts’ Articles

With the development of mobile Internet, We Media was born. WeChat Official Account Platform is the largest we media platform in China. In WeChat social network, information can only be rapidly spread through the sharing operation of users. This paper takes WeChat official accounts as the object and uses logistic regression model to explore the influencing factors on sharing. After that, a prediction model is constructed based on logistic regression and support vector machine. The significance of this study is to propose the factors that influence WeChat official accounts’ articles sharing, and to construct a sharing prediction model

Dilated Context Integrated Network with Cross-Modal Consensus for Temporal Emotion Localization in Videos

Understanding human emotions is a crucial ability for intelligent robots to provide better human-robot interactions. The existing works are limited to trimmed video-level emotion classification, failing to locate the temporal window corresponding to the emotion. In this paper, we introduce a new task, named Temporal Emotion Localization in videos~(TEL), which aims to detect human emotions and localize their corresponding temporal boundaries in untrimmed videos with aligned subtitles. TEL presents three unique challenges compared to temporal action localization: 1) The emotions have extremely varied temporal dynamics; 2) The emotion cues are embedded in both appearances and complex plots; 3) The fine-grained temporal annotations are complicated and labor-intensive. To address the first two challenges, we propose a novel dilated context integrated network with a coarse-fine two-stream architecture. The coarse stream captures varied temporal dynamics by modeling multi-granularity temporal contexts. The fine stream achieves complex plots understanding by reasoning the dependency between the multi-granularity temporal contexts from the coarse stream and adaptively integrates them into fine-grained video segment features. To address the third challenge, we introduce a cross-modal consensus learning paradigm, which leverages the inherent semantic consensus between the aligned video and subtitle to achieve weakly-supervised learning. We contribute a new testing set with 3,000 manually-annotated temporal boundaries so that future research on the TEL problem can be quantitatively evaluated. Extensive experiments show the effectiveness of our approach on temporal emotion localization. The repository of this work is at https://github.com/YYJMJC/Temporal-Emotion-Localization-in-Videos.Comment: Accepted by ACM Multimedia 202

Body composition parameters correlate with the endoscopic severity in Crohn’s disease patients treated with infliximab

BackgroundThe disease activity status and behavior of Crohn’s disease (CD) can reflect the severity of the disease, and changes in body composition are common in CD patients.AimsThe aim of this study was to investigate the relationship between body composition parameters and disease severity in CD patients treated with infliximab (IFX).MethodsPatients with CD assessed with the simple endoscopic score (SES-CD) and were treated with IFX were retrospectively collected, and body composition parameters at the level of the 3rd lumbar vertebrae were calculated from computed tomography (CT) scans of the patients. The correlation of patients’ body composition parameters with disease activity status and disease behavior was analyzed, and the diagnostic value of the relevant parameters was assessed using receiver operating characteristic (ROC) curves.ResultsA total of 106 patients were included in this study. There were significant differences in the subcutaneous adiposity index (SAI) (p = 0.010), the visceral adiposity index (VAI) (p < 0.001), the skeletal muscle mass index (SMI) (p < 0.001), and decreased skeletal muscle mass (p < 0.001) among patients with different activity status. After Spearman and multivariate regression analysis, SAI (p = 0.006 and p = 0.001), VAI (p < 0.001 and p < 0.001), and SMI (p < 0.001and p = 0.007) were identified as independent correlates of disease activity status (both disease activity and moderate-to-severe activity), with disease activity status independently positively correlated with SAI and SMI and independently negatively correlated with VAI. In determining the disease activity and moderate-to-severe activity status, SMI performed best relative to SAI and VAI, with areas under the ROC curve of 0.865 and 0.801, respectively. SAI (p = 0.015), SMI (p = 0.011) and decreased skeletal muscle mass (p = 0.027) were significantly different between different disease behavior groups (inflammatory disease behavior group, complex disease behavior group) but were not independent correlates (p > 0.05).ConclusionBody composition parameters of CD patients treated with IFX correlate with the endoscopic disease severity, and SMI can be used as a reliable indicator of disease activity status

Dynamic constitutive relationship of TiZrHfCu0.5 high entropy alloy based on Johnson-Cook model

High entropy alloy has attracted much attention in the field of national defense due to their excellent low-temperature dynamic mechanical properties. Taking TiZrHfCu0.5 high entropy alloy as the research object, the compressive properties of the specimens under quasi-static and dynamic (strain rate range 600s−1-2600s−1 and temperature range −60 °C–20 °C) conditions are systematically tested. Based on the static/dynamic stress-strain experimental results, the parameters of the original Johnson-Cook constitutive model are determined by fitting. On this basis, a modified Johnson-Cook constitutive model considering the coupling effects of strain, strain rate and temperature is proposed and its parameters are determined. The dynamic compression process of the specimens under different strain rates and temperatures is numerically simulated by ABAQUS finite element software, and the accuracy of the modified Johnson-Cook constitutive model to predict the dynamic compression behavior of TiZrHfCu0.5 high entropy alloy is verified. The experimental and numerical simulation results show that the TiZrHfCu0.5 high entropy alloy exhibits significant strain rate hardening effect and excellent low-temperature mechanical properties during dynamic compression. The ultimate stress can reach 1.79 GPa at −20 °C and strain rate of 2600 s−1. The predicted curves of the modified Johnson-cook constitutive model are in good agreement with the experimental results at low temperature and high strain rate. The modified Johnson-Cook constitutive model is embedded in the finite element software, which effectively improves the reliability of the numerical simulation of the compression performance of TiZrHfCu0.5 high entropy alloy at high strain rate and low temperature. The relative error between the predicted results of the modified Johnson-Cook constitutive model and the experimental results is greatly reduced

Statistical analysis of solar radio fiber bursts and relations with flares

Fiber bursts are a type of fine structure that frequently occurs in solar flares. Although observations and theory of fiber bursts have been studied for decades, their microphysical process, emission mechanism, and especially the physical links with the flaring process still remain unclear. We performed a detailed statistical study of fiber bursts observed by the Chinese Solar Broadband Radio Spectrometers in Huairou with high spectral-temporal resolutions in the frequency ranges of 1.10−2.06 GHz and 2.60−3.80 GHz during 2000−2006. We identify more than 900 individual fiber bursts in 82 fiber events associated with 48 solar flares. From the soft X-ray observations of the Geostationary Operational Environmental Satellite, we found that more than 40% of fiber events occurred in the preflare and rising phases of the associated solar flares. Most fiber events are temporally associated with hard X-ray bursts observed by RHESSI or microwave bursts observed by the Nobeyama Radio Polarimaters, which implies that they are closely related to the nonthermal energetic electrons. The results indicate that most fiber bursts have a close temporal relation with energetic electrons. Most fiber bursts are strongly polarized, and their average duration, relative bandwidth, and relative frequency-drift rate are about 1.22 s, 6.31%, and −0.069 s−1. The average duration and relative bandwidth of fiber bursts increase with solar flare class. The fiber bursts associated with X-class flares have a significantly lower mean relative frequency-drift rate. The average durations in the postflare phase are clearly longer than the duration in the preflare and rising phases. The relative drift rate in the rising phase is clearly higher than that in preflare and postflare phases. The hyperbola correlation of the average duration and the relative drift rate of the fiber bursts is very interesting. These characteristics are very important for understanding the formation of solar radio fiber bursts and for revealing the nonthermal processes of the related solar flares

Maternal postnatal confinement practices and postpartum depression in Chinese populations: A systematic review.

BackgroundThe postpartum period is critical for maternal health status after childbirth. The traditional Chinese postpartum confinement practice, "doing-the-month", is considered especially effective in helping mothers recover during the postpartum period. However, research has not provided evidence to confirm its benefits. Postpartum depression is a common postpartum disease that seriously threatens maternal health. The systematic review aims to explore the association between "doing-the-month" and postpartum depression in the Chinese female population and to provide a scientific foundation for evidence-based postpartum maternal care.MethodsFive databases (PubMed, Embase, Web of Science, Scopus, Cochrane, PsycINFO, and Web of Science) were searched according to the protocol (INPALSY202320102). The JBI assessment tool was used to assess the quality of the included studies.ResultsSixteen quantitative studies from China and Chinese female immigrants in other countries, including 15 cross-sectional studies and 1 randomized controlled study, were identified. Four studies indicated that "doing-the-month" rituals reduced postpartum depression risk while 2 studies showed opposite results; 10 studies did not show a significant association between "doing-the-month" practices and postpartum depression.ConclusionThere is conflicting evidence regarding the association between "doing-the-month" and the likelihood of developing postpartum depression. Some studies have explored the impact of family ties, particular rituals, and specific stressors during the postpartum period on the occurrence of postpartum depression in Chinese women. According to current research, "doing-the-month" practice failed to show a significant protective effect on postpartum depression in the Chinese maternal population. Evidence-based medical health education for the Chinese postpartum female community is urgently needed