Aporias, Transcendence and a Curriculum of Hospitality

Engaging in dynamic encounters with the other and otherness in education—an issue of creating an aperture that welcomes “a newcomer” either as a new idea or new practice—is important for the field of curriculum studies. Complicating aporias as “various forms of other and otherness,” this paper focuses on the encounters with other and otherness (as our understanding of transcendence or border crossing), in which transcendence (border crossing) becomes possible when a curriculum of hospitality is enacted. While culturally and historically informed, the curriculum of hospitality stresses the simultaneity of (1) ethical attentiveness to the encounters with other and otherness, (2) understanding the premise on which hospitality can be enacted—equality and humility and (3) autobiography as possible enacted form of the curriculum. As a curriculum counterpart (Pinar, 2011), curriculum of hospitality centralizes ethical attentiveness to encounters with other and otherness that makes transcendence (space carving) possible, the possible enactment of which is autobiography. It emphasizes the responsibility of educators for welcoming students into a particular world of ideas, knowledge, and skills that honors otherness with hospitality

Dynamic Dense Graph Convolutional Network for Skeleton-based Human Motion Prediction

Graph Convolutional Networks (GCN) which typically follows a neural message passing framework to model dependencies among skeletal joints has achieved high success in skeleton-based human motion prediction task. Nevertheless, how to construct a graph from a skeleton sequence and how to perform message passing on the graph are still open problems, which severely affect the performance of GCN. To solve both problems, this paper presents a Dynamic Dense Graph Convolutional Network (DD-GCN), which constructs a dense graph and implements an integrated dynamic message passing. More specifically, we construct a dense graph with 4D adjacency modeling as a comprehensive representation of motion sequence at different levels of abstraction. Based on the dense graph, we propose a dynamic message passing framework that learns dynamically from data to generate distinctive messages reflecting sample-specific relevance among nodes in the graph. Extensive experiments on benchmark Human 3.6M and CMU Mocap datasets verify the effectiveness of our DD-GCN which obviously outperforms state-of-the-art GCN-based methods, especially when using long-term and our proposed extremely long-term protocol

Spoofing attack augmentation: can differently-trained attack models improve generalisation?

A reliable deepfake detector or spoofing countermeasure (CM) should be robust in the face of unpredictable spoofing attacks. To encourage the learning of more generaliseable artefacts, rather than those specific only to known attacks, CMs are usually exposed to a broad variety of different attacks during training. Even so, the performance of deep-learning-based CM solutions are known to vary, sometimes substantially, when they are retrained with different initialisations, hyper-parameters or training data partitions. We show in this paper that the potency of spoofing attacks, also deep-learning-based, can similarly vary according to training conditions, sometimes resulting in substantial degradations to detection performance. Nevertheless, while a RawNet2 CM model is vulnerable when only modest adjustments are made to the attack algorithm, those based upon graph attention networks and self-supervised learning are reassuringly robust. The focus upon training data generated with different attack algorithms might not be sufficient on its own to ensure generaliability; some form of spoofing attack augmentation at the algorithm level can be complementary.Comment: Accepted to ICASSP 202

A Two-Wheeled Self-Balancing Robot with the Fuzzy PD Control Method

A two-wheeled self-balancing robot with a fuzzy PD control method is described and analyzed as an example of a high-order, multiple-variable, nonlinear, strong-coupling, and unstable system. Based on a system structure model, a kinetic equation is constructed using Newtonian dynamics and mechanics. After a number of simulation experiments, we get the best , , and state-feedback matrices. Then a fuzzy PD controller is designed for which the position and speed of the robot are inputs and for which the angle and angle rate of the robot are controlled by a PD controller. Finally, this paper describes a real-time control platform for the two-wheeled self-balancing robot that controls the robot effectively, after some parameter debugging. The result indicates that the fuzzy PD control algorithm can successfully achieve self-balanced control of the two-wheeled robot and prevent the robot from falling

Association of age and night flight duration with sleep disorders among Chinese airline pilots

ObjectiveNight flights might aggravate sleep disorders among aging airline pilots, posing a threat to flight safety. In this study, we assess the prevalence of sleep disorders as well as the combined effects of night flight duration and aging on sleep disorders.MethodA cross-sectional study was conducted between July and December, 2021. Participants were recruited from a commercial airline. Sleep disorders were evaluated using the Pittsburgh Sleep Quality Index (PSQI). The interaction effect of night flight duration and age on sleep disorders and their correlates were examined using logistic regression models.ResultsIn total, 1,208 male airline pilots were included in the study, with a median age of 34 (interquartile range [IQR]: 29–39) years. The overall prevalence of sleep disorders was 42.6%. The multivariate logistic regression identified an interaction between night flight duration and age on sleep disorders (adjusted odds ratio [aOR] of the interaction term was 5.85 95% CI: 2.23–15.34 for age ≥ 45 years; 1.96 95% CI:1.01–3.81 for the age group 30–44 years). Longer night flight duration (aOR: 4.55; 95%CI: 1.82–11.38) and body mass index (BMI) ≥28.0 kg/m2 (aOR: 0.16; 95% CI: 0.03–0.91) were significantly associated with sleep disorders in participants aged ≥45 years. Hyperuricemia (aOR: 1.54; 95% CI: 1.09–2.16) and regular exercise (aOR: 0.23; 95% CI: 0.08–0.70) were significantly associated with sleep disorders in the 30–44 years age group.ConclusionThe mean monthly night flight duration and aging had a synergistic effect on airline pilots’ sleep disorders, implying an aging and work-related mechanistic pathogenesis of sleep disorders in airline pilots that requires additional exploration and intervention

Long Non-Coding RNA Urothelial Carcinoma Associated 1 Promotes Proliferation, Migration and Invasion of Osteosarcoma Cells by Regulating microRNA-182

Background/Aims: Previous studies demonstrated the oncogenic roles of lncRNA UCA1 in osteosarcoma. This study aimed to explore the internal molecular mechanism of UCA1 on promoting osteosarcoma cell proliferation, migration and invasion. Methods: qRT-PCR was conducted to measure the expression levels of UCA1, miR-182 and TIMP2. Cell transfection was used to change the expression levels of UCA1, miR-182 and TIMP2. Cell viability, migration, invasion and apoptosis were measured using CCK-8 assay, two-chamber migration (invasion) assay and Guava Nexin assay, respectively. The associations between UCA1, miR-182 and iASPP were analyzed by dual luciferase activity assay. The protein expression levels of key factors involved in cell apoptosis, PI3K/AKT/GSK3β pathway and NF-κB pathway, as well as p53, Rb, RECQ family and iASPP were evaluated by western blotting. Results: UCA1 was highly expressed in osteosarcoma MG63 and OS-732 cells. Knockdown of UCA1 inhibited OS-732 cell viability, migration and invasion, but promoted cell apoptosis. miR-182 was up-regulated in OS-732 cells after UCA1 knockdown and participated in the effects of UCA1 on OS-732 cells. TIMP2 was downstream factor of miR-182 and involved in the regulatory roles of miR-182 on OS-732 cell viability, migration, invasion, apoptosis, as well as PI3K/AKT/GSK3β and NF-κB pathways. UCA1 knockdown up-regulated p53, Rb and RECQL5 levels in OS-732 cells, while down-regulated the expression of iASPP. TGF-β or TNF-α treatment could enhance the expression of UCA1 in OS-732 cells. Conclusion: Our research verified that UCA1 exerted oncogenic roles in osteosarcoma cells by regulating miR-182 and TIMP2, as well as PI3K/AKT/GSK3β and NF-κB pathways

Robust Kernel-Based Tracking with Multiple Subtemplates in Vision Guidance System

The mean shift algorithm has achieved considerable success in target tracking due to its simplicity and robustness. However, the lack of spatial information may result in its failure to get high tracking precision. This might be even worse when the target is scale variant and the sequences are gray-levels. This paper presents a novel multiple subtemplates based tracking algorithm for the terminal guidance application. By applying a separate tracker to each subtemplate, it can handle more complicated situations such as rotation, scaling, and partial coverage of the target. The innovations include: (1) an optimal subtemplates selection algorithm is designed, which ensures that the selected subtemplates maximally represent the information of the entire template while having the least mutual redundancy; (2) based on the serial tracking results and the spatial constraint prior to those subtemplates, a Gaussian weighted voting method is proposed to locate the target center; (3) the optimal scale factor is determined by maximizing the voting results among the scale searching layers, which avoids the complicated threshold setting problem. Experiments on some videos with static scenes show that the proposed method greatly improves the tracking accuracy compared to the original mean shift algorithm