Notes

Prolonged non‑coding RNA HCG11 curbs the particular malignant phenotype regarding non‑small mobile united states cellular material through focusing on a miR‑875/SATB2 axis.
Cognitive workload, as measured by the NASA-Task Load Index, was significantly higher in the Nino® than in participants' manual wheelchairs. Findings from qualitative interviews suggest that the Nino® is unlikely to be suitable as a functional replacement of an individual's manual wheelchair. Most participants felt unsafe during braking. Other perceptions included that the Nino may be a good alternative for use as a recreational outdoor mobility device, a powered mobility option to help prevent upper extremity overuse injuries, have a positive impact on social interactions, but that a high degree of focus was required during use. In addition to needing to address safety, usability, and functional concerns, the data suggests a clinical focus on training individuals to use these new devices may be necessary for effective community use.Augmented reality (AR) may be a useful technique to overcome issues of conventionally used navigation systems supporting medical needle insertions, like increased mental workload and complicated hand-eye coordination. Previous research primarily focused on the development of AR navigation systems designed for specific displaying devices, but differences between employed methods have not been investigated before. To this end, a user study involving a needle insertion task was conducted comparing different AR display techniques with a monitor-based approach as baseline condition for the visualization of navigation information. A video see-through stationary display, an optical see-through head-mounted display and a spatial AR projector-camera-system were investigated in this comparison. Results suggest advantages of using projected navigation information in terms of lower task completion time, lower angular deviation and affirmative subjective participant feedback. Techniques requiring the intermediate view on screens, i.e. the stationary display and the baseline condition, showed less favorable results. Thus, benefits of providing AR navigation information compared to a conventionally used method could be identified. Significant objective measures results, as well as an identification of advantages and disadvantages of individual display techniques contribute to the development and design of improved needle navigation systems.Video person re-identification (video Re-ID) plays an important role in surveillance video analysis and has gained increasing attention recently. However, existing supervised methods require vast labeled identities across cameras, resulting in poor scalability in practical applications. Although some unsupervised approaches have been exploited for video Re-ID, they are still in their infancy due to the complex nature of learning discriminative features on unlabelled data. In this paper, we focus on one-shot video Re-ID and present an iterative local-global collaboration learning approach to learning robust and discriminative person representations. Specifically, it jointly considers the global video information and local frame sequence information to better capture the diverse appearance of the person for feature learning and pseudo-label estimation. Moreover, as the cross-entropy loss may induce the model to focus on identity-irrelevant factors, we introduce the variational information bottleneck as a regularization term to train the model together. It can help filter undesirable information and characterize subtle differences among persons. Since accuracy cannot always be guaranteed for pseudo-labels, we adopt a dynamic selection strategy to select part of pseudo-labeled data with higher confidence to update the training set and re-train the learning model. During training, our method iteratively executes the feature learning, pseudo-label estimation, and dynamic sample selection until all the unlabeled data have been seen. Extensive experiments on two public datasets, i.e., DukeMTMC-VideoReID and MARS, have verified the superiority of our model to several cutting-edge competitors.Recently, super-harmonic ultrasound imaging technology has caused much attention due to its capability of distinguishing microvessels from the tissues surrounding them. However, the fabrication of a dual-frequency confocal transducer is still a challenge. In this work, 270- [Formula see text] PMN-PT single crystal 1-3 composite and 28- [Formula see text] PVDF thick film, acting as transmission layer and receiving layer, respectively, are integrated in a novel co-focusing structure. To realize delicate wave propagation control, microwave transmission line theory is introduced to design such structure. Two acoustic filter layers, 13- [Formula see text] copper layer and 39- [Formula see text] Epoxy 301 layer, are indispensable and should be added between two piezoelectric layers. Therefore, an acoustic issue can be overcome via an electrical method and the successful achievement of a dual-frequency (5 MHz/30 MHz) ultrasound transducer with a confocal distance of 8 mm can be realized. The super-harmonic ultrasound imaging experiment is conducted using this kind of device. The 3-D image of 110- [Formula see text]-diameter phantom tube injected with microbubbles can be obtained. These promising results demonstrate that this novel dual-frequency (5 MHz/30 MHz) confocal ultrasound transducer is potentially usable for microvascular medical imaging application in the future.Brain surface analysis is essential to neuroscience, however, the complex geometry of the brain cortex hinders computational methods for this task. The difficulty arises from a discrepancy between 3D imaging data, which is represented in ---Euclidean space---, and the ---non-Euclidean--- geometry of the highly-convoluted brain surface. Recent advances in machine learning have enabled the use of neural networks for non-Euclidean spaces. These facilitate the learning of surface data, yet pooling strategies often remain constrained to a single fixed-graph. This paper proposes a new learnable graph pooling method for processing multiple surface-valued data to output subject-based information. The proposed method innovates by learning an intrinsic aggregation of graph nodes based on graph spectral embedding. We illustrate the advantages of our approach with in-depth experiments on two large-scale benchmark datasets. The ablation study in the paper illustrates the impact of various factors affecting our learnable pooling method. The flexibility of the pooling strategy is evaluated on four different prediction tasks, namely, subject-sex classification, regression of cortical region sizes, classification of Alzheimer's disease stages, and brain age regression. Our experiments demonstrate the superiority of our learnable pooling approach compared to other pooling techniques for graph convolution networks, with results improving the state-of-the-art in brain surface analysis.Experimental games model situations in which the future outcomes of individuals and groups depend on their own choices and on those of other (groups of) individuals. Games are a powerful tool to identify the neural and psychological mechanisms underlying interpersonal and group cooperation and coordination. Here we discuss recent developments in how experimental games are used and adapted, with an increased focus on repeated interactions, partner control through sanctioning, and partner (de)selection for future interactions. Important advances have been made in uncovering the neurobiological underpinnings of key factors involved in cooperation and coordination, including social preferences, cooperative beliefs, (emotion) signaling, and, in particular, reputations and (in)direct reciprocity. Emerging trends at the cross-sections of psychology, economics, and the neurosciences include an increased focus on group heterogeneities, intergroup polarization and conflict, cross-cultural differences in cooperation and norm enforcement, and neurocomputational modeling of the formation and updating of social preferences and beliefs.How do we go about learning new information? This article reviews the importance of practicing retrieval of newly experienced information if one wants to be able to retrieve it again in the future. find more Specifically, practicing retrieval shortly after learning can slow the forgetting process. This benefit can be seen across various material types, and it seems prevalent in all ages and learner abilities and on all types of test. It can also be used to enhance student learning in a classroom setting. I review theoretical understanding of this phenomenon (sometimes referred to as the testing effect or as retrieval-based learning) and consider directions for future research.Humans are an ultrasocial species. This sociality, however, cannot be fully explained by the canonical approaches found in evolutionary biology, psychology, or economics. Understanding our unique social psychology requires accounting not only for the breadth and intensity of human cooperation but also for the variation found across societies, over history, and among behavioral domains. Here, we introduce an expanded evolutionary approach that considers how genetic and cultural evolution, and their interaction, may have shaped both the reliably developing features of our minds and the well-documented differences in cultural psychologies around the globe. We review the major evolutionary mechanisms that have been proposed to explain human cooperation, including kinship, reciprocity, reputation, signaling, and punishment; we discuss key culture-gene coevolutionary hypotheses, such as those surrounding self-domestication and norm psychology; and we consider the role of religions and marriage systems. Empirically, we synthesize experimental and observational evidence from studies of children and adults from diverse societies with research among nonhuman primates.Separating cathode material and Al foil from spent lithium-ion batteries (LIBs) is a critical step for LIBs recycling. As compared to chemical dissolving and decomposition, the pyrolysis pretreatment is an alternative and simple method. In this work, the pyrolysis kinetics of cathode material were comparatively studied using various isoconversional methods, including Flynn-Wall-Ozawa (FWO), Friedman, Kissinger-Akahira-Sunose, Starink, Tang and Boswell. The thermal degradation mechanism was investigated by the Coats-Redfern (CR) and master-plot methods as well. The thermogravimetric analysis revealed that cathode material decomposition could be divided into three stages with mass losses of 1.51%, 0.787% and 0.449%, respectively. Activation energy (Eα) calculated using the six model-free methods showed a similar trend, gradually increasing as the degree of conversion (α) increased from 0.001 to 0.009, and then significantly elevating. The FWO method gave the best fitting and Eα values first increased from 12.032 to 24.433 kJ·mol-1 with α elevating from 0.001 to 0.009, then increased further to 43.187 kJ·mol-1. Both CR and Criado methods indicated that the degradation of cathode material can be explained by the diffusion models. Implication Statement The rapid growth in the production and consumption of lithium ion batteries (LIBs) for portable electronic devices and electric vehicles has resulted in an increasing number of spent LIBs. Thermal treatment offers advantages of high-efficiency and simple operation. Understanding the thermal process of spent LIBs and probing its kinetic are significant for the large-scale treatment. Through this study, it will be significant for the reactor designing and optimizing in practice.
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