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We use the eROSITA Final Equatorial-Depth Survey (eFEDS) to measure the rest-frame 0.1–2.4 keV band X-ray luminosities of ∼600 000 DESI groups using two different algorithms in the overlap region of the two observations. These groups span a large redshift range of 0.0 ≤ zg ≤ 1.0 and group mass range of $10^{10.76}\, h^{-1}\, \mathrm{M}_{\odot } \le M_h \le 10^{15.0}\, h^{-1}\, \mathrm{M}_{\odot }$. (1) Using the blind detection pipeline of eFEDS, we find that 10932 X-ray emission peaks can be cross-matched with our groups, ∼38 per cent of which have a signal-to-noise ratio $\rm {S}/\rm {N} \ge 3$ in X-ray detection. Comparing to the numbers reported in previous studies, this matched sample size is a factor of ∼6 larger. (2) By stacking X-ray maps around groups with similar masses and redshifts, we measure the average X-ray luminosity of groups as a function of halo mass in five redshift bins. We find that in a wide halo mass range, the X-ray luminosity, LX, is roughly linearly proportional to Mh and quite independent to the redshift of the groups. (3) We use a Poisson distribution to model the X-ray luminosities obtained using two different algorithms and obtain the best-fit $L_{\rm X}=10^{28.46\pm 0.03}M_{\rm h}^{1.024\pm 0.002}$ and $L_{\rm X}=10^{26.73 \pm 0.04}M_{\rm h}^{1.140 \pm 0.003}$ scaling relations, respectively. The best-fit slopes are flatter than the results previously obtained but closer to a self-similar prediction.

 

Based on a large group/cluster catalog recently constructed from the DESI Legacy Imaging Surveys DR9 using an extended halo-based group finder, we measure and model the group–galaxy weak-lensing signals for groups/clusters in a few redshift bins within redshift range 0.1 ≤z< 0.6. Here, the background shear signals are obtained based on the DECaLS survey shape catalog, derived with the Fourier_Quadmethod. We divide the lens samples into five equispaced redshift bins and seven mass bins, which allow us to probe the redshift and mass dependence of the lensing signals, and hence the resulting halo properties. In addition to these sample selections, we also check the signals around different group centers, e.g., the brightest central galaxy, the luminosity-weighted center, and the number-weighted center. We use a lensing model that includes off-centering to describe the lensing signals that we measure for all mass and redshift bins. The results demonstrate that our model predictions for the halo masses, biases, and concentrations are stable and self-consistent among different samples for different group centers. Taking advantage of the very large and complete sample of groups/clusters, as well as the reliable estimations of their halo masses, we provide measurements of the cumulative halo mass functions up to redshiftz= 0.6, with a mass precision at 0.03 ∼ 0.09 dex.

 

We present results from a qualitative study involving eight intergenerational families (27 participants) to understand how a family tracking intervention can help support care among intergenerational family members. Our findings show that family members communicate and stay aware of each other's' health through shared fitness data and conversations triggered by fitness sharing. We identified different challenges and preferences among the three age groups in our study: older adults enjoyed family fitness sharing but often encountered various technical challenges, the middle-aged group served as a key person to care for the rest of the family members, and the young generation could not fully engage in fitness sharing due to their busy schedule and privacy concerns. These findings suggest the design of family fitness sharing to account for the age differences in intergenerational families and support the unique needs of family fitness sharing. 

The research community on the study and design of systems for personal informatics has grown over the past decade. To take stock of what the topics the field has studied and methods the field has used, we map and label 523 publications from ACM's library, IEEE Xplore, and PubMed. We surface that the literature has focused on studying and designing for health and wellness domains, an emphasis on understanding and overcoming barriers to data collection and reflection, and progressively fewer contributions involving artifacts being made. Our mapping review suggests directions future research could explore, such as identifying and resolving barriers to tracking stages beyond collection and reflection, engaging more with domain experts, and further discussing the privacy and ethical concerns around tracked data.