Physical environment research of the family ward for a healthy residential environment

Climate change and population aging are two of the most important global health challenges in this century. A 2020 study by the Environmental Protection Agency showed that average people, particularly older adults, spent 90% of their time at home. This is even more evident during the coronavirus disease 2019 (COVID-19) pandemic. Home-based care models have become a new trend. The health and comfort of the living environment profoundly impacts the well-being of older adults. Therefore, research on the physical environment of the family wards has become an inevitable part of promoting the health of older adults; however, current research is still lacking. Based on the study and analysis of continuous monitoring data related to elements of the physical environment (thermal comfort, acoustic quality, lighting quality, and indoor air quality) of family wards, this paper explores the living behaviors of the participants in this environmental research (open or closed windows, air conditioning, artificial lighting, and television) on the indoor physical environment. (1) While referring to the requirements of international standards for an indoor aging-friendly physical environment, we also discuss and analyze the physical environment parameter values according to Chinese standards. (2) People's life behaviors have different degrees of influence on the elements of indoor physical environments. For example, opening doors and windows can alleviate the adverse effects of indoor environmental quality on the human body better than simply turning on the air conditioner. (3) Owing to the decline in physical function, older adults need special care. Studying the status quo of physical environmental elements and proposing suitable environmental improvement measures for aging are of great significance. (4) This research aims to address global warming and severe aging and to contribute to sustainable environmental development

Rethinking Context Aggregation in Natural Image Matting

For natural image matting, context information plays a crucial role in estimating alpha mattes especially when it is challenging to distinguish foreground from its background. Exiting deep learning-based methods exploit specifically designed context aggregation modules to refine encoder features. However, the effectiveness of these modules has not been thoroughly explored. In this paper, we conduct extensive experiments to reveal that the context aggregation modules are actually not as effective as expected. We also demonstrate that when learned on large image patches, basic encoder-decoder networks with a larger receptive field can effectively aggregate context to achieve better performance.Upon the above findings, we propose a simple yet effective matting network, named AEMatter, which enlarges the receptive field by incorporating an appearance-enhanced axis-wise learning block into the encoder and adopting a hybrid-transformer decoder. Experimental results on four datasets demonstrate that our AEMatter significantly outperforms state-of-the-art matting methods (e.g., on the Adobe Composition-1K dataset, \textbf{25\%} and \textbf{40\%} reduction in terms of SAD and MSE, respectively, compared against MatteFormer). The code and model are available at \url{https://github.com/QLYoo/AEMatter}

Learning Dynamic Mechanisms in Unknown Environments: A Reinforcement Learning Approach

Dynamic mechanism design studies how mechanism designers should allocate resources among agents in a time-varying environment. We consider the problem where the agents interact with the mechanism designer according to an unknown Markov Decision Process (MDP), where agent rewards and the mechanism designer's state evolve according to an episodic MDP with unknown reward functions and transition kernels. We focus on the online setting with linear function approximation and propose novel learning algorithms to recover the dynamic Vickrey-Clarke-Grove (VCG) mechanism over multiple rounds of interaction. A key contribution of our approach is incorporating reward-free online Reinforcement Learning (RL) to aid exploration over a rich policy space to estimate prices in the dynamic VCG mechanism. We show that the regret of our proposed method is upper bounded by $\tilde{\mathcal{O}}(T^{2/3})$ and further devise a lower bound to show that our algorithm is efficient, incurring the same $\tilde{\mathcal{O}}(T^{2 / 3})$ regret as the lower bound, where $T$ is the total number of rounds. Our work establishes the regret guarantee for online RL in solving dynamic mechanism design problems without prior knowledge of the underlying model.Comment: Minor Revision for JMLR. The first three authors contribute equall

Detection of TiO and VO in the atmosphere of WASP-121b and Evidence for its temporal variation

We report the transit observations of the ultra hot Jupiter WASP-121b using the Goodman High Throughput Spectrograph (GHTS) at the 4-meter ground-based telescope Southern Astrophysical Research Telescope (SOAR), covering the wavelength range $502-900$ nm. By dividing the target and reference star into 19 spectroscopic passbands and applying differential spectrophotometry, we derive spectroscopic transit light curves and fit them using Gaussian process framework to determine transit depths for every passbands. The obtained optical transmission spectrum shows a steep increased slope toward the blue wavelength, which seems to be too steep to be accounted for by the Rayleigh scattering alone. We note that the transmission spectrum from this work and other works differ obviously from each other, which was pointed out previously by \citet{Wilson2021} as evidence for temporal atmospheric variation. We perform a free chemistry retrieval analysis on the optical transmission spectra from this work and the literature HST/WFC3 NIR spectrum. We determine TiO, VO and H$_{2}$O with abundances of $-5.95_{-0.42}^{+0.47}$ dex, $-6.72_{-1.79}^{+0.51}$ dex, and $-4.13_{-0.46}^{+0.63}$ dex, respectively. We compare the abundances of all these three molecules derived from this work and previous works, and find that they are not consistent with each other, indicating the chemical compositions of the terminator region may change over long timescales. Future multi-epoch and high-precision transit observations are required to further confirm this phenomena. We note that when combining the transmission spectra in the optical and in NIR in retrieval analysis, the abundances of V and VO, the NIR-to-optical offset and the cloud deck pressure may be coupled with each other.Comment: 23 pages, 13 figures, 6 tables. Accepted for publication in Research in Astronomy and Astrophysic

Thermal Emission from the Hot Jupiter WASP-103b in JJ and KsK_{\rm s} Bands

Hot Jupiters, particularly those with temperature higher than 2000\,K are the best sample of planets that allow in-depth characterization of their atmospheres. We present here a thermal emission study of the ultra hot Jupiter WASP\mbox{-}103\,b observed in two secondary eclipses with CFHT/WIRCam in $J$ and $K_{\rm s}$ bands. By means of high precision differential photometry, we determine eclipse depths in $J$ and $K_{\rm s}$ to an accuracy of 220 and 270\,ppm, which are combined with the published HST/WFC3 and Spitzer data to retrieve a joint constraints on the properties of WASP-103\,b dayside atmosphere. We find that the atmosphere is best fit with a thermal inversion layer included. The equilibrium chemistry retrieval indicates an enhanced C/O (1.35$^{+0.14}_{-0.17}$) and a super metallicity with [Fe/H]$=2.19^{+0.51}_{-0.63}$ composition. Given the near-solar metallicity of WASP-103 of [Fe/H]=0.06, this planet seems to be $\sim$100 more abundant than its host star. The free chemistry retrieval analysis yields a large abundance of FeH, H$^{-}$, CO$_2$ and CH$_4$. Additional data of better accuracy from future observations of JWST should provide better constraint of the atmospheric properties of WASP-103b

Simulation study of BESIII with stitched CMOS pixel detector using ACTS

Reconstruction of tracks of charged particles with high precision is very crucial for HEP experiments to achieve their physics goals. As the tracking detector of BESIII experiment, the BESIII drift chamber has suffered from aging effects resulting in degraded tracking performance after operation for about 15 years. To preserve and enhance the tracking performance of BESIII, one of the proposals is to add one layer of thin CMOS pixel sensor in cylindrical shape based on the state-of-the-art stitching technology, between the beam pipe and the drift chamber. The improvement of tracking performance of BESIII with such an additional pixel detector compared to that with only the existing drift chamber is studied using the modern common tracking software ACTS, which provides a set of detector-agnostic and highly performant tracking algorithms that have demonstrated promising performance for a few high energy physics and nuclear physics experiments