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Chen Peng and Mike Ryczek begin their paintings with meticulous observation. Peng studies the objects of her daily life, looking for something that provokes an emotional response; Ryczek scours surveillance footage online, searching for the perfect fleeting moment. Although the artists are driven by different impulses, they both use this process as a means of understanding.
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Held in collaboration between KEF and Lane Crawford, the 10 Asian Designers To Watch exhibition will be held in Shanghai from March 31 to April 11 in an effort to spotlight the most promising young talents in fashion across Asia. Highlighting the role of sound and music both to inspire and bolster the power of fashion, the KEF Experience Zone will allow attendees to engage with the latest cutting-edge audio technology to transport the mind within the headspace of the designers. Find out more online here.
Objective: The goals were twofold: To estimate the depression and anxiety levels among caregivers of patients with eating disorders (ED) in China during the COVID-19 pandemic when compared with a control group, and to assess whether an online education program was effective in decreasing the anxiety and depression of the caregivers of patients with ED, and associated factors.
Method: Caregivers of patients with ED (n = 254) and a comparison group of non-ED caregivers (N = 254) were recruited at baseline. Additionally, caregivers of patients with ED were invited into a free 4-week online education program, with an additional online group as support. Depression and anxiety levels were assessed at baseline and after the intervention.
Results: Caregivers of patients with ED showed significantly higher levels of depression and anxiety than the comparison group of non-ED caregivers. The online education program showed no significant effect on decreasing depression and anxiety levels of caregivers of patients with ED overall. Caregivers who had older loved ones and not living with them were more likely to decrease their depression levels. Caregivers of patients with longer illness duration were less likely to decrease their anxiety levels.
Discussion: These results showed that caregivers of ED patients suffered more serious psychological distress during the pandemic. A more structured and intensive online intervention with a limited number of participants might be required to address caregivers' distress in post-COVID-19 China.
I am a fourth-year PhD student (Fall 2019 - present) in the computer science department of Columbia University, advised by Christos Papadimitriou and Xi Chen. I am broadly interested in theoretical computer science, especially its intersection with machine learning and game theory. In summer 2022, I visited Stanford university and worked with Aviad Rubinstein. I visited Simons Institute (Berkerley) in Spring 2022 for the Learning and games program. In summer 2020, I worked in Google research NYC, hosted by Sara Ahmadian. I got my bachelor degree from Yao class, Tsinghua Univeristy, where I worked with Pingzhong Tang on game theory. I worked on online algorithms with Anupam Gupta and Zhiyi Huang when I visited CMU and HKU. I have also worked on influence maximization with Wei Chen when I worked as an intern in MSRA.
Chen has petitioned local officials, protested and then was detained for three days, as Marketplace reported. He even released a song about the injustice homebuyers face, but it changed nothing except that his song is now censored online.
Feature point tracking deals with image streams that change over time. Most existing feature point tracking algorithms only consider two adjacent frames at a time, and forget the feature information of previous frames. In this paper, we present a new eigenspace-based tracking method that learns an eigenspace representation of training features online, and finds the target feature point with Gauss-Newton style search method. A coarse-to-fine processing strategy is introduced to handle large affine transformations. Several simulations and experiments on real images indicate the effectiveness of the proposed feature tracking algorithm under the conditions of large pose changes and temporary occlusions. 041b061a72