Dreamcore originates from a video (or image) form submitted on 21 April 2018, when an anonymous user posted a thread on 4chan’s paranormal section collecting images that would make people feel ‘uncomfortable', and another user’s comment under it gained the attention of the community. And it has been a new subculture that uses familiar scenes to make the audience nostalgic but uneasy, with two important characteristics: ‘Lost items’ and ‘exposed shame’. In contrast to the philosophical concept ‘sense of material’, the (...) absolutely independent defamiliarization, or liminal space’s ‘neither … nor … ’, ‘lost items’ pursues the familiarity in strangeness without resorting to the expression of magical reality, or using ambiguity between the two to create a ‘either … or …’ atmosphere; Compared with modern urban planning based on the principle of ‘ecology’, ‘exposed shame’ reveals infrastructures that do not match the natural setting in the image, causing abruptness and embarrassment. Both point to the dreamcore’s playful ambiguity, thus not being governed by serious art and symbolising the original intention of free creation. (shrink)

Eye-tracking technology has become a powerful tool for biomedical-related applications due to its simplicity of operation and low requirements on patient language skills. This study aims to use the machine-learning models and deep-learning networks to identify key features of eye movements in Alzheimer's Disease (AD) under specific visual tasks, thereby facilitating computer-aided diagnosis of AD. Firstly, a three-dimensional (3D) visuospatial memory task is designed to provide participants with visual stimuli while their eye-movement data are recorded and used to build an (...) eye-tracking dataset. Then, we propose a novel deep-learning-based model for identifying patients with Alzheimer's Disease (PwAD) and healthy controls (HCs) based on the collected eye-movement data. The proposed model utilizes a nested autoencoder network to extract the eye-movement features from the generated fixation heatmaps and a weight adaptive network layer for the feature fusion, which can preserve as much useful information as possible for the final binary classification. To fully verify the performance of the proposed model, we also design two types of models based on traditional machine-learning and typical deep-learning for comparison. Furthermore, we have also done ablation experiments to verify the effectiveness of each module of the proposed network. Finally, these models are evaluated by four-fold cross-validation on the built eye-tracking dataset. The proposed model shows 85% average accuracy in AD recognition, outperforming machine-learning methods and other typical deep-learning networks. (shrink)

IntroductionRace-walking is a sport that mimics normal walking and running. Previous studies on sports science mainly focused on the cardiovascular and musculoskeletal systems. However, there is still a lack of research on the central nervous system, especially the real-time changes in brain network characteristics during race-walking exercise. This study aimed to use a network perspective to investigate the effects of different exercise intensities on brain functional connectivity.Materials and methodsA total of 16 right-handed healthy young athletes were recruited as participants in (...) this study. The cerebral cortex concentration of oxyhemoglobin was measured by functional near-infrared spectroscopy in the bilateral prefrontal cortex (PFC), the motor cortex (MC) and occipital cortex (OC) during resting and race-walking states. Three specific periods as time windows corresponding to different exercise intensities were divided from the race-walking time of participants, including initial, intermediate and sprint stages. The brain activation and functional connectivity (FC) were calculated to describe the 0.01-0.1 Hz frequency-specific cortical activities.ResultsCompared to the resting state, FC changes mainly exist between MC and OC in the initial stage, while PFC was involved in FC changes in the intermediate stage, and FC changes in the sprint stage were widely present in PFC, MC and OC. In addition, from the initial-development to the sprint stage, the significant changes in FC were displayed in PFC and MC.ConclusionThis brain functional connectivity-based study confirmed that hemodynamic changes at different exercise intensities reflected different brain network-specific characteristics. During race-walking exercise, more extensive brain activation might increase information processing speed. Increased exercise intensity could facilitate the integration of neural signals such as proprioception, motor control and motor planning, which may be an important factor for athletes to maintain sustained motor coordination and activity control at high intensity. This study was beneficial to understanding the neural mechanisms of brain networks under different exercise intensities. (shrink)

In order to improve the impact resistance and mechanical performance of anchor rods and satisfy the requirements for supporting rockburst roadways, the energy balance equation of the energy-absorbing support and roadway surrounding rock system is established. Moreover, to effectively prevent rockburst disasters, the energy criterion for roadway instability is derived. From the perspective of an energy-absorbing support, a yield-absorbing anti-shock anchor composed of a rod body, tray, constant resistance energy-absorbing device, and special-shaped nut is designed and developed; compared with ordinary (...) anchor rods, this rod has stronger mechanical properties for resisting impact. Theoretical and numerical simulation studies show that the energy-absorbing device has a repeatable deformation failure mode and a constant yield force. The paper also presents the principle involved in the design of anti-shock bolt supports. The energy-absorbing support not only effectively guides and controls the release and conversion of impact energy but also consumes the impact energy in the buffering process of the anchor to ensure the stability of surrounding rock and support protection system. This study aims to provide reference for roadway support design and to improve rock bolts used in rockburst roadways. (shrink)

Tumor necrosis factor (TNF) receptor associated factor 6 (TRAF6) is a crucial signaling molecule regulating a diverse array of physiological processes, including adaptive immunity, innate immunity, bone metabolism and the development of several tissues including lymph nodes, mammary glands, skin and the central nervous system. It is a member of a group of six closely related TRAF proteins, which serve as adapter molecules, coupling the TNF receptor (TNFR) superfamily to intracellular signaling events. Among the TRAF proteins, TRAF6 is unique in (...) that, in addition to mediating TNFR family signaling, it is also essential for signaling downstream of an unrelated family of receptors, the interleukin‐1 (IL‐1) receptor/Toll‐like receptor (IL‐1R/TLR) superfamily. Gene targeting experiments have identified several indispensable physiological functions of TRAF6, and structural and biochemical studies have revealed the potential mechanisms of its action. By virtue of its many signaling roles, TRAF6 represents an important target in the regulation of many disease processes, including immunity, inflammation and osteoporosis. BioEssays 25:1096–1105, 2003. © 2003 Wiley Periodicals, Inc. (shrink)