Microwave and hard X-ray emissions during the impulsive phase of solar flares: Nonthermal electron spectrum and time delay

On the basis of the summing-up and analysis of the observations and theories about the impulsive microwave and hard X-ray bursts, the correlations between these two kinds of emissions were investigated. It is shown that it is only possible to explain the optically-thin microwave spectrum and its relations with the hard X-ray spectrum by means of the nonthermal source model. A simple nonthermal trap model in the mildly-relativistic case can consistently explain the main characteristics of the spectrum and the relative time delays

BTS & ARMY: A South Korean Music Group and their Fandom Create a New Grassroots Movement for Social Change

This study links the discourse analysis of social innovation, social entrepreneurship, and cultural analysis of BTS--a South Korean music group--and their global fan base--ARMY. Despite its diversity in form, the current narrative of social innovation in academia has been limited to western market constructs, business, or technological innovations, while the process of social innovation remains under-researched. The BTS and ARMY movement has been a growing study in scholarship, as their collaborative efforts redefine a new form of human connection through digital intimacy, creating a grassroots movement for social and cultural revolution. By integrating and analyzing diverse concepts of social innovation literature with a variety of scholarship, the BTS and ARMY movement is a prime case study of a non-western framework for the process of social innovation. Their collaborative efforts and togetherness not only challenge the Western-dominated music hegemony but proved that non-western subjects and/or subjectivities are deconstructing definitions of culture, creativity, and social innovation exclusive to western frameworks. This asserts that non-western cultures, like Asia, can be a changeable force to the west, and western hegemony can no longer be a dominant force in the global context

The Impact of Child Abuse, Posttraumatic Cognitions, Machiavellianism and Emotional Suppression on Interpersonal Sensitivity and Psychiatric Comorbidity: A Latent Profile Analysis

Much of the detrimental effects child abuse can have on victims’ cognitions, personality traits and emotional regulation strategies have been documented; however, it is unclear whether these effects might coexist with posttraumatic cognitions, Machiavellianism, and emotional suppression to impact interpersonal sensitivity and psychiatric comorbidity. The present study aimed to address this knowledge gap. A sample of 553 Chinese university students from three universities completed the Childhood Trauma Questionnaire-short form, Posttraumatic Cognitions Inventory, Machiavellianism Personality scale, Courtauld Emotional Control Scale, Interpersonal Sensitivity Measure, and General Health Questionnaire-28. Using Latent Profile Analysis, a three-profile solution was achieved. Profile one (high maltreatment group) students reported high levels of abusive experiences, posttraumatic cognitions and Machiavellianism, but a moderate level of emotional suppression; Profile two (moderate maltreatment group) students had moderate levels of abusive experiences, posttraumatic cognitions, Machiavellianism and emotional suppression. Profile three (low maltreatment group) students had low levels of all of the preceding psychological constructs. Profile one reported significantly higher interpersonal sensitivity and psychiatric comorbidity. Students with child abuse experiences, who viewed themselves and others negatively, displayed some dark personality traits, exercised some control over their emotions, tended to be excessively sensitive to others’ behaviors and feelings and prone to psychological distress

Social Network Model for Accessing and Sharing Expertise During Disasters

Whether human-made or natural disasters, both could typically followed by chaos, this often results from an inadequate overall response. Preparedness is the best response to emergencies, and a multi-agent-based approach to coordination decision support systems often plays a significant role in disaster management and response. Using an integrated approach to facilitate coordination is considered important in dealing with disasters. Often, there are different kinds of coordination, such as physical coordination between emergent agencies or local agencies, and administrative coordination. While traditional disaster management studies have focused on coordination of managerial or government policy approaches, this study focuses on the direct local-based advice network used by emergency personnel (such as managers and volunteers) to understand how the properties of such human networks affect the ability to access and share expertise during a disaster incident in order to ensure prompt and accurate decisions. The key motivating question guiding this research is: how can the multi-level study of properties of social networks at network, actor and tie level help us understand the coordination that enables expertise access and sharing during disasters? Moreover, this study also asks: To what degree is this relationship associated with expertise coordination in a negative or positive manner? How are centralisation and efficiency in an individual’s social network associated with coordination? Do network constraints and tie strength in an individual’s social network negatively or positively affect coordination? This study uses novel theoretical approaches to suggest an empirical-based framework and methodology for exploring the relationship between the properties of social networks and coordination of expertise during disasters

Persistent Homology in Sparse Regression and its Application to Brain Morphometry

Sparse systems are usually parameterized by a tuning parameter that determines the sparsity of the system. How to choose the right tuning parameter is a fundamental and difficult problem in learning the sparse system. In this paper, by treating the the tuning parameter as an additional dimension, persistent homological structures over the parameter space is introduced and explored. The structures are then further exploited in speeding up the computation using the proposed soft-thresholding technique. The topological structures are further used as multivariate features in the tensor-based morphometry (TBM) in characterizing white matter alterations in children who have experienced severe early life stress and maltreatment. These analyses reveal that stress-exposed children exhibit more diffuse anatomical organization across the whole white matter region.Comment: submitted to IEEE Transactions on Medical Imagin

Adoption of robotic assisted partial nephrectomies: a population-based analysis of U.S. surgeons from 2004-2013

The advent of minimally invasive and robotic techniques has resulted in the rapid adoption of this novel technology, with the field of urology at the forefront. Since the first Robotic‐Assisted Laparoscopic Radical Prostatectomy (RALP) was performed in 2000 using  the da Vinci Surgical System (Intuitive Surgical, Inc., Sunnyvale, CA, USA), surgeons have rapidly incorporated robotic technology for the use of radical prostatectomies for prostatic carcinoma. Prior to 2005, only a minority of surgeons‐‐fewer than 2.5%‐‐performing radical  prostatectomies utilized robotic assistance.  However, robotic assistance has become the predominant approach for radical prostatectomies, increasing from 22% to 85% between the years 2002 to 2013, representing a nearly five‐fold increase in utilization

A Novel Lockable Spring-loaded Prismatic Spine to Support Agile Quadrupedal Locomotion

This paper introduces a way to systematically investigate the effect of compliant prismatic spines in quadrupedal robot locomotion. We develop a novel spring-loaded lockable spine module, together with a new Spinal Compliance-Integrated Quadruped (SCIQ) platform for both empirical and numerical research. Individual spine tests reveal beneficial spinal characteristics like a degressive spring, and validate the efficacy of a proposed compact locking/unlocking mechanism for the spine. Benchmark vertical jumping and landing tests with our robot show comparable jumping performance between the rigid and compliant spines. An observed advantage of the compliant spine module is that it can alleviate more challenging landing conditions by absorbing impact energy and dissipating the remainder via feet slipping through much in cat-like stretching fashion.Comment: To appear in 2023 IEEE IRO

The concept of self among Chinese university victims of child abuse: an interpretative phenomenological analysis

The impact of child abuse experiences on the concept of self has been documented, however, using the qualitative method to further understand the subjective experiences of victims’ self-concept has not been done. Ten participants aged 19 to 22 reporting a history of child abuse experiences provided subjective feelings of the effects following these experiences in the form of a semi-structured interview. Using interpretative phenomenological analysis (IPA), there were 5 superordinate themes, including self-perceptions, negative perceptions of others/ the world, difficulties in interpersonal relationships, emotional regulation skills and personal characteristics in the present study. The results showed that (1) victims had some negative perceptions of themselves and of others but also had some positive self-perceptions. (2) Victims had some maladaptive characteristics, such as amorality or manipulation, for self-protection and maintaining social harmony; (3) and they easily suppressed their non-anger emotions. (4) They encountered social and intimate relationship difficulties. The subjective feelings of child abuse victims explored many negative perceptions of the self and others and showed the sensitivity of rejection in interpersonal relationships. Some negative personal characteristics and emotional suppression were also found among victims

Direct Diffusion Bridge using Data Consistency for Inverse Problems

Diffusion model-based inverse problem solvers have shown impressive performance, but are limited in speed, mostly as they require reverse diffusion sampling starting from noise. Several recent works have tried to alleviate this problem by building a diffusion process, directly bridging the clean and the corrupted for specific inverse problems. In this paper, we first unify these existing works under the name Direct Diffusion Bridges (DDB), showing that while motivated by different theories, the resulting algorithms only differ in the choice of parameters. Then, we highlight a critical limitation of the current DDB framework, namely that it does not ensure data consistency. To address this problem, we propose a modified inference procedure that imposes data consistency without the need for fine-tuning. We term the resulting method data Consistent DDB (CDDB), which outperforms its inconsistent counterpart in terms of both perception and distortion metrics, thereby effectively pushing the Pareto-frontier toward the optimum. Our proposed method achieves state-of-the-art results on both evaluation criteria, showcasing its superiority over existing methods. Code is available at https://github.com/HJ-harry/CDDBComment: NeurIPS 2023 camera-ready. 16 pages, 6 figure