Risk factors associated with online game addiction: A hierarchical model

Online gaming addiction has been increasingly recognized as a mental disorder. However, the predictive factors that lead to online gaming addiction are not well established. The aim of this study was to identify factors that may influence the development of online gaming addiction. A total of 263 patients with problematic online gaming addiction (255 males (97%) and 8 females (3%), age: mean = 20.4 ± 5.8 years) and153 healthy comparison subjects (118 males (77%) and 35 females (23%), age: 21.2 ± 5.5 years, range) were recruited for participation in the current study. Hierarchical logistic regression analyses among each set of variables were conducted. Individual factors (sex and age), cognitive factors (IQ and perseverative errors), psychopathological conditions (ADHD, depression, anxiety, and impulsivity), and social interaction factors (family environment, social anxiety, and self-esteem) were evaluated in a stepwise fashion. All four factors were associated with online gaming addiction, with psychopathological conditions being the strongest risk factors for the addiction. Individual factors, psychological factors, and social interactions were associated with the development of pure online gaming addiction. As before, psychological factors (attention, mood, anxiety and impulsivity) were the strongest risk factors for online gaming addiction in patients with pure online gaming addiction. Psychopathologies, including ADHD and depression, were the strongest factors associated with the development of online gaming addiction in individuals.     

The benefit of being physically present: A survey of experimental works comparing copresent robots,telepresent robots and virtual agents

The effects of physical embodiment and physical presence were explored through a survey of 33 experimental works comparing how people interacted with physical robots and virtual agents. A qualitative assessment of the direction of quantitative effects demonstrated that robots were more persuasive and perceived more positively when physically present in a user׳s environment than when digitally-displayed on a screen either as a video feed of the same robot or as a virtual character analog; robots also led to better user performance when they were collocated as opposed to shown via video on a screen. However, participants did not respond differently to physical robots and virtual agents when both were displayed digitally on a screen – suggesting that physical presence, rather than physical embodiment, characterizes people׳s responses to social robots. Implications for understanding psychological response to physical and virtual agents and for methodological design are discussed.     

Modeling surface water-groundwater interaction in arid and semi-arid regions with intensive agriculture

In semi-arid and arid areas with intensive agriculture, surface water-groundwater (SW-GW) interaction and agricultural water use are two critical and closely interrelated hydrological processes. However, the impact of agricultural water use on the hydrologic cycle has been rarely explored by integrated SW-GW modeling, especially in large basins. This study coupled the Storm Water Management Model (SWMM), which is able to simulate highly engineered flow systems, with the Coupled Ground-Water and Surface-Water Flow Model (GSFLOW). The new model was applied to study the hydrologic cycle of the Zhangye Basin, northwest China, a typical arid to semi-arid area with significant irrigation. After the successful calibration, the model produced a holistic view of the hydrological cycle impact by the agricultural water use, and generated insights into the spatial and temporal patterns of the SW-GW interaction in the study area. Different water resources management scenarios were also evaluated via the modeling. The results showed that if the irrigation demand continuous to increase, the current management strategy would lead to acceleration of the groundwater depletion, and therefore introduce ecological problems to this basin. Overall, this study demonstrated the applicability of the new model and its value to the water resources management in arid and semi-arid areas.     

A hand gesture recognition technique for human–computer interaction

We propose an approach to recognize trajectory-based dynamic hand gestures in real time for human–computer interaction (HCI). We also introduce a fast learning mechanism that does not require extensive training data to teach gestures to the system. We use a six-degrees-of-freedom position tracker to collect trajectory data and represent gestures as an ordered sequence of directional movements in 2D. In the learning phase, sample gesture data is filtered and processed to create gesture recognizers, which are basically finite-state machine sequence recognizers. We achieve online gesture recognition by these recognizers without needing to specify gesture start and end positions. The results of the conducted user study show that the proposed method is very promising in terms of gesture detection and recognition performance (73% accuracy) in a stream of motion. Additionally, the assessment of the user attitude survey denotes that the gestural interface is very useful and satisfactory. One of the novel parts of the proposed approach is that it gives users the freedom to create gesture commands according to their preferences for selected tasks. Thus, the presented gesture recognition approach makes the HCI process more intuitive and user specific.     

TAF-ID: An international thermodynamic database for nuclear fuels applications

The Thermodynamics of Advanced Fuels – International Database (TAF-ID) was developed using the Calphad method to provide a computational tool to perform thermodynamic calculations on nuclear fuel materials under normal and off-normal conditions. Different kinds of fuels are considered: oxide, metallic, carbide and nitride fuels. Many fission products are introduced as well as structural materials (e.g., zirconium, steel, concrete, SiC) and absorbers (e.g., B₄C), in order to investigate the thermochemistry of irradiated fuels and to predict their chemical interaction with the surrounding materials. The approach to develop the database and the models implemented in the database are described. Examples of models for key chemical systems are presented. Finally, a few examples of application calculations on severe accidents with UO₂ fuels, irradiated fuel chemistry of MOX and metallic fuels and metallic fuel/cladding interaction show how this tool can be used. To validate the database, the calculations are compared to the available experimental data. A good agreement is obtained which gives confidence in the maturity degree and quality of the TAF-ID database. The working version is only accessible to the participants of the TAF-ID project (Canada, France, Japan, the Netherlands, Republic of Korea, United Kingdom, USA). A public version is accessible by all the NEA countries. The current version contains models on the Am–Fe, Am–Np, Am-O-Pu, Am–U, Am–Zr, C–O–U-Pu, Cr–U, Np–U, Np–Zr, O–U–Zr, Re–U, Ru–U, Si–U, Ti–U, U-Pu-Zr, U–W systems. It is progressively extended with our published assessments. Information on how to join the project is available on the website: https://www.oecd-nea.org/science/taf-id/.     

Design for comfort and social interaction in future vehicles: A study on the leg space between facing-seats configuration

With the advent of future vehicles, passengers expect to travel in comfort, and the free leg space between facing-seats could be an issue due to the unsuitability for all people, according to their anthropometric variability. A previous investigation survey showed the need to increase the leg-space between facing seats and, if installed, to improve the surface of the table placed in between. So, four different distances between seat-pans front edges of facing seats have been set-up and tested (44 cm, 51 cm, 58 cm, 65 cm) with a table in between. 13 couples of participants with different heights took part to experiments. The aim was to investigate the relationship between facing-seat distances and passenger wellbeing in terms of postural comfort and social interaction. Postural comfort has been analysed through optical tracking (for postural angles overtime) and questionnaires (perceived comfort). Social interaction feelings have been investigated with questionnaires. Experiment results showed the suitable distance could be 51 cm keeping the same table surface; otherwise, the 65 cm one could be ideal changing the table surface.Relevance to industryWith the advent of autonomous driving, vehicle manufacturers and designers are working hard to define new paradigms of public transportation in terms of seat layout, passenger wellbeing and interiors’ design. This paper contributes to increasing the general knowledge on the effects of distance between facing seats on postural comfort and social interaction.     

Stress intensity factor evaluations for a curved crack in orthotropic particulate composites using an interaction integral method

This paper develops a domain-independent interaction integral (DII-integral) for extracting mixed-mode stress intensity factors (SIFs) for orthotropic materials with complex interfaces. The DII-integral does not require material property gradients, and moreover its validity is not affected by material interfaces. Combined with the extended finite element method (XFEM), the DII-integral is employed to investigate a straight crack in an orthotropic functionally graded plate and a curved crack in orthotropic particulate composites.     

基于卷积神经网络优化TLD运动手势跟踪算法

针对TLD（Tracking-Learning-Detection）算法在光照变化不均、遮挡严重、跟踪目标模糊等情况下会出现跟踪失败的问题，提出一种基于卷积神经网络优化TLD运动手势跟踪算法。选取手势特征作正样本，其背景作负样本，获取手势HOG特征并投入到卷积神经网络中加以训练，得到手势检测分类器，从而确定目标手势区域，实现手势的自动识别；再利用TLD算法对手势进行跟踪与学习，对正负样本进行估计检测并实时校正，同时运用SURF特征匹配更新跟踪器。实验结果验证，该算法对比TLD经典算法跟踪精度提高了4.24%，增强了运动手势的跟踪效果，相比经典跟踪算法拥有更高鲁棒性。     

Quantifying co-creative writing experiences

Collaboration with artificial intelligence (AI) is a growing trend even in the field of creativity. This paper examines which quantitative metrics can be used to comparatively analyse human-computer co-creativity with children. To study this question, 24 schoolchildren of age 10–11 wrote a poem with three co-creative poetry writing processes: a human-computer, a human-human, and a human-human-computer process. The computational participant in the processes was an AI-based application called the Poetry Machine. The children were asked to evaluate their user experience with a 5-point Likert-type questionnaire after each writing process and a comparative questionnaire after finishing all processes. The metrics used in the evaluation were immediate fun, long-term enjoyment, creativity, self-expression, outcome satisfaction, ease of starting and finishing writing, quality of ideas and support from others, and ownership.

Significant differences were found in fun, long-term enjoyment, quality of ideas, support, and ownership. The high number of statistically relevant results was enabled by exposing all participants to all writing processes, and the comparative questionnaire. The human-human-computer process was evaluated the best in long-term enjoyment and the human-computer process the weakest in support and idea quality. Creativity and ease of finishing writing turned out to be outlining metrics for the co-creative processes.