The Quasi-normal Modes of Charged Scalar Fields in Kerr-Newman black hole and Its Geometric Interpretation

It is well-known that there is a geometric correspondence between high-frequency quasi-normal modes (QNMs) and null geodesics (spherical photon orbits). In this paper, we generalize such correspondence to charged scalar field in Kerr-Newman space-time. In our case, the particle and black hole are all charged, so one should consider non-geodesic orbits. Using the WKB approximation, we find that the real part of quasi-normal frequency corresponds to the orbits frequency, the imaginary part of the frequency corresponds to the Lyapunov exponent of these orbits and the eigenvalue of angular equation corresponds to carter constant. From the properties of the imaginary part of quasi-normal frequency of charged massless scalar field, we can still find that the QNMs of charged massless scalar field possess the zero damping modes in extreme Kerr-Newman spacetime under certain condition which has been fixed in this paper.Comment: 30 pages, many figures, to appear in JHE

Family Depression Profiles Among Adolescents and Their Parents: A Group-Based Multi-Trajectory Modeling

Early onset of depression predicts unfavorable psychosocial and health outcomes, and depression often co-occurs for children and their parents, yet family profiles of depression trajectories are not fully examined. This population-based longitudinal prospective cohort study included 2,111 families drawn from the Chinese Family Panel Study (CFPS) with biannual assessments from 2010 to 2018. Group-based multi-trajectory modeling was used to identify depression trajectories of children, fathers, and mothers. Six distinct profiles of depression symptoms were identified. Based upon multi-trajectory findings of family depression profiles, when adolescents are at risk for depression, there is likely at least one parent concurrently at risk for depression, but not vice versa. Families with social disadvantages and children of delayed developmental milestones are at elevated risk for depression. Even when children are at low risk for depression, depression in parents can spill over to impact other psychosocial and health outcomes. These findings suggest examining depression and its associating psychosocial factors could help identify trajectories of varying onset and continuity, which can inform early prevention and intervention from a family system perspective

Developmental Funding and Nurturing in Colleges and Universities in the New Era: Dilemmas - Paths - Significance

Doing a good job of financial aid and education in colleges and universities can help consolidate the results of China's current poverty alleviation efforts, combining "poverty alleviation with helping the wise and the ambitious" to achieve the goal of "blood transfusion", but also "blood-creation", to help students from economically disadvantaged families successfully complete their studies, and to maintain national security and stability. To help students with family economic difficulties to successfully complete their studies, to achieve social justice, and to maintain national security and stability. This paper explores the problems faced by colleges and universities in the new era in promoting the development of financial support for people, and proposes solutions to the great significance of developmental funding. Push the funding to a more in-depth development, to help students grow and achieve success, to achieve the overall development of students

Engine Vibration Certification

AbstractEngine vibration is an important factor for aircraft to ensure flight safety. Based on the analysis of each airworthiness requirement revision's background, connotation and technical essential factors on engine vibration, and combined with the engine vibration certification analysis on the existing model approved, the process and main point for the engine vibration certification will be given in this paper

Prevalence of Common Mental Health Concerns and Service Utilization Among International Students Studying in the U.S.

An estimated one million international students are enrolled in U.S. universities. However, little was known about the landscape of their mental health and help-seeking behaviors. Drawing from a large national university student sample (N = 228,421, 8.49% non-U.S. citizen) from the Healthy Minds Study, data indicated the rates of major depressive disorder, generalized anxiety disorder, eating disorder, non-suicidal self-injury, and suicidal ideation were 27.4%, 20.0%, 26.4%, 17.2%, and 8.8% respectively among international students, with high inter-country variabilities. Contrary to our expectations, there is no strong and consistent evidence suggesting international students were at higher risk for common mental health concerns compared to domestic students. However, among students who were screened positive for these mental health disorders (n = 96,567), there was a significant difference between service utilization rates for international students and domestic students (32.0% vs. 49.8%), even after controlling for gender, age, socioeconomic status, perceived need for help, mental health stigma, and using informal support. Our results highlight the urgency for addressing mental health concerns and equitable mental health care among international students

Why gender matters in CMC: gender differences in remote trust and performance with initial social activities

Gender effects in face-to-face and virtual communications are well known in the discipline of communication studies. However, less attention has been paid to the effects of gender on carrying out complex, collaborative tasks in virtual environments, mediated by modern communication media. The primary objective of this research is to explore gender differences in synchronous computer-mediated communication (CMC) with and without initial social activities. In particular, it aims to investigate whether exposure to pre-task social activities before doing a task can help males, who tend to be less trusting, overcome the trust barrier.This research combines theories and empirical findings from a wide range of disciplines, including CMC, gender, trust and communication. One hundred and twenty four participants who did not previously know each other were recruited to form homogeneous pairs, male-male and female-female. Each pair carried out a competitive task via Instant Messaging (IM), either with or without pre-task social chat. The results from both quantitative and qualitative analyses indicate that female pairs had high levels of trust and more collaborative behaviors than male pairs in doing the task. In addition, females’ collaborative conversational style focusing on harmonious relationships put them in a position to achieve trust in the communication. The results also suggest that initial social chat prior to beginning work helps remote team members build trust in the communication. But that initial social chat is more effective in female dominated groups.The results have implications for research and practice of establishing higher levels of trust among remote workers who have to communicate via low-end media. In addition, this research will add to the small, but growing body of literature on the effects of group gender composition on performance outcomes. It will also benefit designers understanding emoticon usage patterns and developing design criteria for creating usable and useful interactive chat systems that support trust of both genders.Ph.D., Information Science and Technology -- Drexel University, 200

Overlooked Poses Actually Make Sense: Distilling Privileged Knowledge for Human Motion Prediction

Previous works on human motion prediction follow the pattern of building a mapping relation between the sequence observed and the one to be predicted. However, due to the inherent complexity of multivariate time series data, it still remains a challenge to find the extrapolation relation between motion sequences. In this paper, we present a new prediction pattern, which introduces previously overlooked human poses, to implement the prediction task from the view of interpolation. These poses exist after the predicted sequence, and form the privileged sequence. To be specific, we first propose an InTerPolation learning Network (ITP-Network) that encodes both the observed sequence and the privileged sequence to interpolate the in-between predicted sequence, wherein the embedded Privileged-sequence-Encoder (Priv-Encoder) learns the privileged knowledge (PK) simultaneously. Then, we propose a Final Prediction Network (FP-Network) for which the privileged sequence is not observable, but is equipped with a novel PK-Simulator that distills PK learned from the previous network. This simulator takes as input the observed sequence, but approximates the behavior of Priv-Encoder, enabling FP-Network to imitate the interpolation process. Extensive experimental results demonstrate that our prediction pattern achieves state-of-the-art performance on benchmarked H3.6M, CMU-Mocap and 3DPW datasets in both short-term and long-term predictions.Comment: accepted by ECCV202

DeFeeNet: Consecutive 3D Human Motion Prediction with Deviation Feedback

Let us rethink the real-world scenarios that require human motion prediction techniques, such as human-robot collaboration. Current works simplify the task of predicting human motions into a one-off process of forecasting a short future sequence (usually no longer than 1 second) based on a historical observed one. However, such simplification may fail to meet practical needs due to the neglect of the fact that motion prediction in real applications is not an isolated ``observe then predict'' unit, but a consecutive process composed of many rounds of such unit, semi-overlapped along the entire sequence. As time goes on, the predicted part of previous round has its corresponding ground truth observable in the new round, but their deviation in-between is neither exploited nor able to be captured by existing isolated learning fashion. In this paper, we propose DeFeeNet, a simple yet effective network that can be added on existing one-off prediction models to realize deviation perception and feedback when applied to consecutive motion prediction task. At each prediction round, the deviation generated by previous unit is first encoded by our DeFeeNet, and then incorporated into the existing predictor to enable a deviation-aware prediction manner, which, for the first time, allows for information transmit across adjacent prediction units. We design two versions of DeFeeNet as MLP-based and GRU-based, respectively. On Human3.6M and more complicated BABEL, experimental results indicate that our proposed network improves consecutive human motion prediction performance regardless of the basic model.Comment: accepted by CVPR202

Understanding Text-driven Motion Synthesis with Keyframe Collaboration via Diffusion Models

The emergence of text-driven motion synthesis technique provides animators with great potential to create efficiently. However, in most cases, textual expressions only contain general and qualitative motion descriptions, while lack fine depiction and sufficient intensity, leading to the synthesized motions that either (a) semantically compliant but uncontrollable over specific pose details, or (b) even deviates from the provided descriptions, bringing animators with undesired cases. In this paper, we propose DiffKFC, a conditional diffusion model for text-driven motion synthesis with keyframes collaborated. Different from plain text-driven designs, full interaction among texts, keyframes and the rest diffused frames are conducted at training, enabling realistic generation under efficient, collaborative dual-level control: coarse guidance at semantic level, with only few keyframes for direct and fine-grained depiction down to body posture level, to satisfy animator requirements without tedious labor. Specifically, we customize efficient Dilated Mask Attention modules, where only partial valid tokens participate in local-to-global attention, indicated by the dilated keyframe mask. For user flexibility, DiffKFC supports adjustment on importance of fine-grained keyframe control. Experimental results show that our model achieves state-of-the-art performance on text-to-motion datasets HumanML3D and KIT

On Gravitational anomaly and Hawking radiation near weakly isolated horizon

Based on the idea of the work by Wilczek and his collaborators, we consider the gravitational anomaly near weekly isolated horizon. We find that there exists a universal choice of tortoise coordinate for any weakly isolated horizon. Under this coordinate, the leading behavior of a quite arbitrary scalar field near horizon is a 2-dimensional chiral scalar field. This means we can extend the idea of Wilczek and his collaborators to more general cases and show the relation between gravitational anomaly and Hawking radiation is a universal property of black hole horizon.Comment: 14 page