The influence of different tree densities on alpha waves, physical activity enjoyment, and satisfaction of late middle-aged and older adults using virtual cycling.

Cave automatic virtual environment (CAVE), as a novel approach to promoting physical activity, shows great potential for improving the mental health and healthy lifestyle of older adults. Based on stress reduction theory, tree density is regarded as a main characteristic of a virtual sportscape that will affect the experience and benefits of exercising. However, the effect of tree density on the experience of exercising remains unclear. The current study was undertaken to investigate the effects of tree cover density on the alpha waves induced and the enjoyment and satisfaction derived by engaging in physical activity in a virtual environment. Eighty-seven late middle-aged and older adults were randomly assigned to one of the following conditions: a high tree density sportscape (HTDS = 36-60 %), a medium tree density sportscape, (MTDS = 20-35 %), and a control condition. Questionnaires and electroencephalogram read-outs of alpha waves were used to evaluate the changes in stress levels experienced by the participants before, during, and after 20 min of cycling. The results showed that participants exposed to an HTDS exhibited to physical activity with significantly more enjoyment and satisfaction than those in the MTDS and control groups. In contrast, the highest degree of relaxation was exhibited in the MTDS condition, suggesting that an MTDS is more effective at reducing perceived stress among late middle-aged and older adults engaging in virtual cycling. These findings demonstrate that exercising in a virtual reality setting with different densities of tree cover comes with physiological and psychological wellbeing for late middle-aged and older adults.

Molecular geometry specific Monte Carlo simulation of the efficacy of diamond crystal formation from diamondoids.

Diamondoids are a class of organic molecules with the carbon skeletons isostructural to nano-diamond, and have been shown to be promising precursors for diamond formation. In this work, the formation of diamond crystals from various diamondoid molecule building blocks was studied using our developed molecular geometry specific Monte Carlo method. We maintained the internal carbon skeletons of the diamondoid molecules, and investigated how the carbon-carbon bonds form between diamondoid molecules and how efficient the process is to form diamond crystals. The simulations show that higher diamondoid molecules can produce structures closer to a diamond crystal compared with lower diamondoid molecules. Specifically, using higher diamondoid molecules, larger bulk diamond crystals are formed with fewer vacancies. The higher propensity of certain diamondoids to form diamond crystals reveals insights into the microscopic processes of diamond formation under high-pressure high-temperature conditions.

Traces of electron-phonon coupling in one-dimensional cuprates.

The appearance of certain spectral features in one-dimensional (1D) cuprate materials has been attributed to a strong, extended attractive coupling between electrons. Here, using time-dependent density matrix renormalization group methods on a Hubbard-extended Holstein model, we show that extended electron-phonon (e-ph) coupling presents an obvious choice to produce such an attractive interaction that reproduces the observed spectral features and doping dependence seen in angle-resolved photoemission experiments: diminished 3kF spectral weight, prominent spectral intensity of a holon-folding branch, and the correct holon band width. While extended e-ph coupling does not qualitatively alter the ground state of the 1D system compared to the Hubbard model, it quantitatively enhances the long-range superconducting correlations and suppresses spin correlations. Such an extended e-ph interaction may be an important missing ingredient in describing the physics of the structurally similar two-dimensional high-temperature superconducting layered cuprates, which may tip the balance between intertwined orders in favor of uniform d-wave superconductivity.

Industrial Anomaly Detection with Skip Autoencoder and Deep Feature Extractor.

Over recent years, with the advances in image recognition technology for deep learning, researchers have devoted continued efforts toward importing anomaly detection technology into the production line of automatic optical detection. Although unsupervised learning helps overcome the high costs associated with labeling, the accuracy of anomaly detection still needs to be improved. Accordingly, this paper proposes a novel deep learning model for anomaly detection to overcome this bottleneck. Leveraging a powerful pre-trained feature extractor and the skip connection, the proposed method achieves better feature extraction and image reconstructing capabilities. Results reveal that the areas under the curve (AUC) for the proposed method are higher than those of previous anomaly detection models for 16 out of 17 categories. This indicates that the proposed method can realize the most appropriate adjustments to the needs of production lines in order to maximize economic benefits.

Visual responses of patients with generalized anxiety disorder who cycling in the virtual sportscapes with different tree cover densities.

The tree density of virtual sportscape is the main factor that determines the benefits that generalized anxiety disorder (GAD) patients can obtain when they exercise with virtual environment. By using pupil size, fixation count and time as metrics, this research aimed to clarify the relationship between tree cover density and stress in the virtual environment. Ninety GAD patients were randomly grouped into the 36-60% tree density (high tree density, HTDS), 20-35% tree density (medium tree density, MTDS), or control groups (n = 30). Researchers used eye-tracking technology to analyze fixation time, fixation count and changes in pupil size to evaluate the stress changes of participants after 20 min of aerobic exercise in a virtual environment. The results showed that pupil size expanded in GAD patients after exercising in the virtual environment. Furthermore, GAD patient cycling in the MTDS group can show smaller pupil size than those in HTDS. Those results suggest that GAD patient cycling 20 min in the MTDS group can perceived lower stress. The results of eye tracking analysis showed that GAD patients spend more time and counts observing tree elements in HTDS and MTDS sportscapes. Specifically, they spent more 48% and 27% time on tree and green plants in the HTDS condition and MTDS condition, respectively, than in non-natural sportsscapes. Although 36-60% tree density of virtual natural sportscape can get more visual attention from GAD patients, 20-35% tree density of virtual natural sportscape is more capable of reducing their stress.

Visual Attention, Behavioral Intention, and Choice Behavior Among Older Consumers Toward Sports Marketing Images: An Eye-Tracking Study.

Mental health benefits (i.e., relaxing and relieving pressure) can influence consumers' consumption decisions. However, there is still no clear understanding of the impact of mental health benefits on visual attention, behavioral intention, and choice behavior. Study 1 was thus aimed at exploring the visual attention and behavioral intention of older consumers with respect to exercise consumption. A sample of 186 older consumers was investigated. An eye-tracking analysis was used to evaluate the visual attention of participants observing health promotion messages, and questionnaires were used to assess the behavioral intention of the older consumers under consideration in this work. The findings confirmed that marketing pictures combining natural sportscapes with prevention focus messages (i.e., conveying information to consumers that it is safe and not easy to be injured when engaging in yoga activities in natural settings) can best capture older consumers' visual attention (e.g., fixation numbers and fixation times) and behavioral intentions. In Study 2, 75 participants were recruited. It was found that marketing pictures combining natural sportscapes with prevention focus messages were selected more by the participants, with health communication images successfully attracting them to choose the sports program products being presented. The findings of the two studies suggested that marketing pictures can effectively stimulate consumers' visual attention and has effects on their behavioral intention and choices toward exercising in a safe, natural environment.

The Visual Attention and Psychological Responses from Older Customers to Wellness Service Pictures of Hotels.

Understanding the visual attention and psychological responses of consumers to marketing pictures allows hotel managers to design more attractive advertisements. Therefore, the purposes of the present study were to use an eye-tracking analysis to explore whether there were different effects from tourist hotels' wellness service pictures based on whether they had natural or built clues. The psychological responses with regard to perceived well-being and willingness to pay were also examined. Eighty-five older consumers were recruited. Their eye movement performance while observing marketing pictures with different visual clues and their subsequent psychological responses were measured. It was found that wellness service pictures with natural clues captured more visual attention and induced higher willingness-to-pay perceptions than those with built clues in these older consumers. The present results suggest that marketing pictures with natural clues may create positive visual responses in older customers and further enhance their purchase intention.

Psychological and Physiological Responses in Patients with Generalized Anxiety Disorder: The Use of Acute Exercise and Virtual Reality Environment.

Virtual exercise therapy is considered a useful method by which to encourage patients with generalized anxiety disorder (GAD) to engage in aerobic exercise in order to reduce stress. This study was intended to explore the psychological and physiological responses of patients with GAD after cycling in a virtual environment containing natural images. Seventy-seven participants with GAD were recruited in the present study and randomly assigned to a virtual nature (VN) or a virtual abstract painting (VAP) group. Their electroencephalogram alpha activity, perceived stress, and levels of restorative quality and satisfaction were assessed at baseline and after an acute bout of 20 min of moderate-intensity aerobic exercise. The results showed that both the VN and VAP groups showed significantly higher alpha activity post-exercise as compared to pre-exercise. The VN group relative to the VAP group exhibited higher levels of stress-relief, restorative quality, and personal satisfaction. These findings imply that a virtual exercise environment is an effective way to induce a relaxing effect in patients with GAD. However, they exhibited more positive psychological responses when exercising in such an environment with natural landscapes.

Anomaly Detection Neural Network with Dual Auto-Encoders GAN and Its Industrial Inspection Applications.

Recently, researchers have been studying methods to introduce deep learning into automated optical inspection (AOI) systems to reduce labor costs. However, the integration of deep learning in the industry may encounter major challenges such as sample imbalance (defective products that only account for a small proportion). Therefore, in this study, an anomaly detection neural network, dual auto-encoder generative adversarial network (DAGAN), was developed to solve the problem of sample imbalance. With skip-connection and dual auto-encoder architecture, the proposed method exhibited excellent image reconstruction ability and training stability. Three datasets, namely public industrial detection training set, MVTec AD, with mobile phone screen glass and wood defect detection datasets, were used to verify the inspection ability of DAGAN. In addition, training with a limited amount of data was proposed to verify its detection ability. The results demonstrated that the areas under the curve (AUCs) of DAGAN were better than previous generative adversarial network-based anomaly detection models in 13 out of 17 categories in these datasets, especially in categories with high variability or noise. The maximum AUC improvement was 0.250 (toothbrush). Moreover, the proposed method exhibited better detection ability than the U-Net auto-encoder, which indicates the function of discriminator in this application. Furthermore, the proposed method had a high level of AUCs when using only a small amount of training data. DAGAN can significantly reduce the time and cost of collecting and labeling data when it is applied to industrial detection.

The Effect of Cycling Through a Projection-Based Virtual Environment System on Generalized Anxiety Disorder.

Virtual reality (VR) has the potential to help clinical medicine manage generalized anxiety disorder (GAD). However, patients with GAD who use traditional head-mounted VR to cycle may cause them to feel motion sickness and fatigue. To solve this problem, a projection-based virtual environment (VE) system was built to provide GAD patients with a sense of immersion while they are cycling. This projection-based VE system allows patients with GAD to interact with the virtual environment and produce experiences similar to cycling in the outdoors. Sixty GAD patients met several screening criteria and were selected as participants. All participants were randomly assigned to one of the two 20-min conditions: (1) Observing watercolor paintings projected by the projector while engaged in cycling with a stationary bicycle; or (2) observing the scenes (i.e., forest or park) projected by the VE system and engaging in cycling with a stationary bicycle. Finally, this study confirmed that patients with GAD in the projection-based VE group exhibited higher alpha values and lower galvanic skin responses (GSR) after cycling than those cycling in the control group. These results showed that cycling in the projection-based VE group allowed the patient with GAD to achieve higher exercise intensity and lower perceived emotional stress.

Mediating effect of cooperative norm in predicting organizational citizenship behaviors from procedural justice climate.

Although the relationships between procedural justice climate and organizational citizenship behaviors have been examined in recent years, little research has explored the mechanism by which procedural justice climate shapes individual employee prosocial behaviors in the workplace. The purpose of this study was to examine the mediating role of a group-level cooperative norm on the relationships between the group-level procedural justice climate and individual-level organizational citizenship behaviors. The survey involved 45 work groups in four different industry fields in Taiwan, including manufacturing, technology, banking, and insurance, and each of the groups was composed of one supervisor and three subordinates. Cross-level analyses using hierarchical linear modeling (HLM) indicated that the cooperative norm fully mediated the relationship between procedural justice climate and individual helping behaviors. Procedural justice climate indirectly affects individual helping behaviors through their effects on the cooperative norm.