Relaxation Behavior of Residual Stress on Deck-to-Rib Welded Joints by Fatigue Loading in an Orthotropic Bridge Deck

To accurately evaluate the influence of the actual tension and compression state and stress ratio at the deck-to-rib welding seam position on the fatigue life of a bridge deck, this paper establishes a coupled stress analysis model that considers the welding residual stress and vehicle stress. Taking the Jiangyin Bridge as an example, a qualitative analysis of the fatigue life under the vehicle load and residual stress field is carried out using the proposed method. A case analysis showed that when the residual tensile stress in the welding seam position is superimposed on the mainly tensile cyclic vehicle load stress, the longitudinal stress relaxation exceeds the peak vehicle load stress; significant longitudinal stress relaxation occurred, while the transverse stress relaxation is not significant. However, when the residual tensile stress is superimposed on the mainly compressive cyclic vehicle load stress, the relaxations of both the longitudinal and transverse stresses are not obvious. Compared with the stress state of the welding point under the action of only the vehicle stress, when the coupling effect of the residual stress and vehicle stress is considered, i.e., the loading condition, the fatigue stress state of the weld point has undergone an essential change under cyclic compressive stress, that is, the compressive stress state that does not require a fatigue check is changed to the tensile stress state. Although the fatigue state of the tensile stress cycle condition has not changed, the fatigue life is reduced by varying degrees under either the compressive or tensile condition

Session-Based Recommendation by Exploiting Substitutable and Complementary Relationships from Multi-behavior Data

Session-based recommendation (SR) aims to dynamically recommend items to a user based on a sequence of the most recent user-item interactions. Most existing studies on SR adopt advanced deep learning methods. However, the majority only consider a special behavior type (e.g., click), while those few considering multi-typed behaviors ignore to take full advantage of the relationships between products (items). In this case, the paper proposes a novel approach, called Substitutable and Complementary Relationships from Multi-behavior Data (denoted as SCRM) to better explore the relationships between products for effective recommendation. Specifically, we firstly construct substitutable and complementary graphs based on a user's sequential behaviors in every session by jointly considering `click' and `purchase' behaviors. We then design a denoising network to remove false relationships, and further consider constraints on the two relationships via a particularly designed loss function. Extensive experiments on two e-commerce datasets demonstrate the superiority of our model over state-of-the-art methods, and the effectiveness of every component in SCRM.Comment: 31 pages,11 figures, accepted by Data Mining and Knowledge Discovery(2023

Survey on public awareness, attitudes and self-protective behavior adoption in different periods of COVID-19

IntroductionThe outbreak and spread of the pandemics have been an issue of critical concern globally, posing a significant threat to the health sector globally. This study aimed to examine the basic knowledge and attitudes toward the recommended protective measures at different times, respond to the COVID-19 pandemic, and provide recommendations for developing targeted strategies and measures for preventing and controlling public health emergencies.MethodsThe study used self-filled questionnaires to examine the public's knowledge, attitudes, and practices on COVID-19 at two different period, from 20 to 31 March 2020 (the beginning period) and 22–27 April 2022 (the regular epidemic prevention and control period). Descriptive and quantitative analyses were used for statistical analysis.Results and discussionThe survey collected 2375 valid questionnaires. A comparison of the two periods reveals that as the epidemic continued over a long period, the level of knowledge, attitudes toward preventive measures, risk perceptions, and adoption behavior of the respondents at the beginning of the epidemic were significantly higher than during the regular epidemic prevention and control period. With the upsurge in the spread of the epidemic, the public needs a multi-channel, targeted, and all-round guidance and information on prevention and control of the COVID-19, and internalizes knowledge into individual's behavior of actively responding to diseases.When the epidemic lasts for a long time, the relevant agencies should strengthen their monitoring role to promote public compliance with the recommended measures

Climate Change Impacts on Winter Wheat Yield in Northern China

Exploring the impacts of climate change on agriculture is one of important topics with respect to climate change. We quantitatively examined the impacts of climate change on winter wheat yield in Northern China using the Cobb–Douglas production function. Utilizing time-series data of agricultural production and meteorological observations from 1981 to 2016, the impacts of climatic factors on wheat production were assessed. It was found that the contribution of climatic factors to winter wheat yield per unit area (WYPA) was 0.762–1.921% in absolute terms. Growing season average temperature (GSAT) had a negative impact on WYPA for the period of 1981–2016. A 1% increase in GSAT could lead to a loss of 0.109% of WYPA when the other factors were constant. While growing season precipitation (GSP) had a positive impact on WYPA, as a 1% increase in GSP could result in 0.186% increase in WYPA, other factors kept constant. Then, the impacts on WYPA for the period 2021–2050 under two different emissions scenarios RCP4.5 and RCP8.5 were forecasted. For the whole study area, GSAT is projected to increase 1.37°C under RCP4.5 and 1.54°C under RCP8.5 for the period 2021–2050, which will lower the average WYPA by 1.75% and 1.97%, respectively. GSP is tended to increase by 17.31% under RCP4.5 and 22.22% under RCP8.5 and will give a rise of 3.22% and 4.13% in WYPA. The comprehensive effect of GSAT and GSP will increase WYPA by 1.47% under RCP4.5 and 2.16% under RCP8.5

Annotation method of risk data in a certain field based on pattern matching

With the development of information technology and the increasing complexity of industrial technology, there is an urgent need for a certain field to use big data and artificial intelligence to improve the management and decision-making level. In order to classify the field’s risk text data through intelligent algorithms, analysing the risk distribution and the major problems, this paper researches on the annotation methods of training data in this field. The proposed data annotation method is based on pattern matching, addressing the special problems of risk data annotation in this field (such as strong professionalism, small data volume, high accuracy requirement and timeliness requirements). A new matching pattern is generated through the steps of text segmentation, keyword extraction, pattern preliminary generation, pattern relation tree construction, pattern optimization, pattern generalization, pattern verification, classification and annotation, and final classification and annotation are performed after pattern matching. Performance tests in terms of accuracy, recall rate, and annotation time have shown that the overall performance of the proposed method outperforms that of traditional item-by-item manual annotation, and semi-automatic annotation methods through machine learning. The method described in this paper has strong application value for risk data annotation in this field, and also has certain reference significance for high-density, high-accuracy and high-timeliness data annotation in other fields

A Longitudinal Study of Recurrent Experience of Earthquake and Mental Health Problems Among Chinese Adolescents

Background: The effects of recurrent exposure to disasters on adolescents’ mental health have rarely been studied. We examined the effects of two earthquake experiences 5 years apart in a longitudinal cohort of Chinese adolescents.Methods: A total of 858 adolescents were assessed in September, 2011 (3.5 years after the Wenchuan earthquake, 1.5 years before Ya’an earthquake, T1) and April, 2013 (1 week after the Ya’an earthquake, T2). Participants’ Wenchuan earthquake experiences and symptoms of post-traumatic stress disorder (PTSD) and depression were assessed at T1, and their Ya’an earthquake experiences, Acute Stress Disorder (ASD), PTSD, and depression were assessed at T2.Results: Structural equation models showed a positive relationship between Ya’an earthquake experiences and symptoms of ASD, PTSD, and depression at T2. T1 PTSD symptoms significantly increased T2 ASD, PTSD, and depression symptoms, and also mediated the relationships between Wenchuan earthquake experiences and T2 ASD, PTSD, and depression symptoms. T1 Depression symptoms also significantly increased T2 ASD, PTSD, and depression symptoms, but only mediated the association between Wenchuan earthquake experiences and T2 depression symptoms. In addition, Wenchuan earthquake experiences moderated the effects of Ya’an earthquake experiences on ASD symptoms and PTSD symptoms but not depression.Conclusion: Repeated to exposure to disasters have adverse additive effects on adolescents’ mental health. Adolescents who experience one disaster may be sensitive to the negative impact of subsequent ones

Calculation of microscopic nuclear level densities based on covariant density functional theory

A microscopic method for calculating nuclear level density (NLD) based on the covariant density functional theory (CDFT) is developed. The particle-hole state density is calculated by combinatorial method using the single-particle levels schemes obtained from the CDFT. Then the level densities are obtained by taking into account collective effects such as vibration and rotation. Our results are compared with those from other NLD models, including phenomenological, microstatistical, and non-relativistic HFB combinatorial models. The comparison suggests that the general trends among these models are basically the same, except for some deviations from different NLD models. In addition, the NLDs of the CDFT combinatorial method with normalization are compared with experimental data, including the observed cumulative number of levels at low excitation energy and the measured NLDs. Compared with the existing experimental data, the CDFT combinatorial method can give reasonable results.Comment: 9 pages, 8 figure