Depressive symptoms among older empty nesters in China: the moderating effects of social contact and contact with one’s children

Objectives: Mental health for older people has become a major social concern. Literature has shown that older people, especially when they become empty nesters—when a parent lives alone or lives with his/her spouse after the youngest child leaves home—may start to develop various mental health problems due to reduced contacts with their children. Methods: Using fixed-effects, multivariate regression with a difference-in-differences approach and propensity score matching, this paper examines the relationship between being an empty nester and mental health among older people in China, and the moderating effects of social contact and contact with one’s children in terms of mental health. Our data come from the China Health and Retirement Longitudinal Study of 2011, 2013, 2015 and 2018. Results: We found that, in the short term, the mental health of older people may not be affected after they became empty nesters. But in the longer term, if they did not have regular contact with their children, their mental health would deteriorate with time. Social contact, especially cognitive activities, was beneficial to the mental health of the older empty nesters. We also found that for older empty nesters with disabilities, frequent social contact and contact with their children were more important. Conclusion: We urge the government to promote community-based social activities for older people, especially for those with functional limitations

Communication in Immersive Social Virtual Reality: A Systematic Review of 10 Years' Studies

As virtual reality (VR) technologies have improved in the past decade, more research has investigated how they could support more effective communication in various contexts to improve collaboration and social connectedness. However, there was no literature to summarize the uniqueness VR provided and put forward guidance for designing social VR applications for better communication. To understand how VR has been designed and used to facilitate communication in different contexts, we conducted a systematic review of the studies investigating communication in social VR in the past ten years by following the PRISMA guidelines. We highlight current practices and challenges and identify research opportunities to improve the design of social VR to better support communication and make social VR more accessible.Comment: Chinese CHI '22: The Tenth International Symposium of Chinese CHI (Chinese CHI 2022

Inverse-designed broadband low-loss grating coupler on thick lithium-niobate-on-insulator platform

A grating coupler on 700-nm-thick Z-cut lithium-niobate-on-insulator platform with high coupling efficiency, large bandwidth, and high fabrication tolerance is designed and optimized by inverse design method. The optimized grating coupler is fabricated with a single set of e-beam lithography and etching process, and it is experimentally characterized to possess peak coupling efficiency of -3.8 dB at 1574.93 nm, 1-dB bandwidth of 71.7 nm, and 3-dB bandwidth of over 120 nm.Comment: 8 pages, 4 figure

Synapse: Interactive Guidance by Demonstration with Trial-and-Error Support for Older Adults to Use Smartphone Apps

As smartphones are widely adopted, mobile applications (apps) are emerging to provide critical services such as food delivery and telemedicine. While bring convenience to everyday life, this trend may create barriers for older adults who tend to be less tech-savvy than young people. In-person or screen sharing support is helpful but limited by the help-givers' availability. Video tutorials can be useful but require users to switch contexts between watching the tutorial and performing the corresponding actions in the app, which is cumbersome to do on a mobile phone. Although interactive tutorials have been shown to be promising, none was designed for older adults. Furthermore, the trial-and-error approach has been shown to be beneficial for older adults, but they often lack support to use the approach. Inspired by both interactive tutorials and trial-and-error approach, we designed an app-independent mobile service, \textit{Synapse}, for help-givers to create a multimodal interactive tutorial on a smartphone and for help-receivers (e.g., older adults) to receive interactive guidance with trial-and-error support when they work on the same task. We conducted a user study with 18 older adults who were 60 and over. Our quantitative and qualitative results show that Synapse provided better support than the traditional video approach and enabled participants to feel more confident and motivated. Lastly, we present further design considerations to better support older adults with trial-and-error on smartphones

An improved differential evolution algorithm and its applications to orbit design

Differential Evolution (DE) is a basic and robust evolutionary strategy that has been applied to determining the global optimum for complex optimization problems[1–5]. It was introduced in 1995 by Storn and Price [1] and has been successfully applied to optimization problems including nonlinear, non-differentiable, non-convex, and multi-model functions. DE algorithms show good convergence, high-reliability, simplicity, and a reduced number of controllable parameters [2]. Olds and Kluever [3] applied DE to an interplanetary trajectory optimization problem and demonstrated the effectiveness of DE to produce rapid solutions. Madavan [4] discussed various modifications to the DE algorithm, improved its computational efficiency, and applied it to aerodynamic shape optimization problems. DE algorithms are easy to use, as they require only a few robust control variables, which can be drawn from a well-defined numerical interval. However, the existing various DE algorithms also have limitations, being susceptible to instability and getting trapped into local optima[2]. Notable effort has been spent addressing this by coupling DE algorithms with other optimization algorithms (for example, Self Organizing Maps (SOM) [6], Dynamic Hill Climbing (DHC) [7], Neural Networks (NN) [7], Particle Swarm Optimization (PSO) [8]). In these cases, the additional algorithm is used as an additional loop within the optimization process, creating a hybrid system with an inner and outer loop. Such hybrid algorithms are inherently more complex and so the computation cost is increased. Attempting to address this, a self-adaptive DE was designed and applied to the orbit design problem for prioritized multiple targets by Chen[5]. However, the self-adaptive feature is somewhat limited as it relates only to the number of generations within the optimization. A Self-adaptive DE which can automatically adapt its learning strategies and the associated parameters during the evolving procedure was proposed by Qin and Suganthan[9] and 25 test functions were used to verify the algorithm

Semi-Implicit Denoising Diffusion Models (SIDDMs)

Despite the proliferation of generative models, achieving fast sampling during inference without compromising sample diversity and quality remains challenging. Existing models such as Denoising Diffusion Probabilistic Models (DDPM) deliver high-quality, diverse samples but are slowed by an inherently high number of iterative steps. The Denoising Diffusion Generative Adversarial Networks (DDGAN) attempted to circumvent this limitation by integrating a GAN model for larger jumps in the diffusion process. However, DDGAN encountered scalability limitations when applied to large datasets. To address these limitations, we introduce a novel approach that tackles the problem by matching implicit and explicit factors. More specifically, our approach involves utilizing an implicit model to match the marginal distributions of noisy data and the explicit conditional distribution of the forward diffusion. This combination allows us to effectively match the joint denoising distributions. Unlike DDPM but similar to DDGAN, we do not enforce a parametric distribution for the reverse step, enabling us to take large steps during inference. Similar to the DDPM but unlike DDGAN, we take advantage of the exact form of the diffusion process. We demonstrate that our proposed method obtains comparable generative performance to diffusion-based models and vastly superior results to models with a small number of sampling steps