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The origin of primates has long been associated with an increased emphasis on manual grasping and touch. Precision touch, facilitated by specialized mechanoreceptors in glabrous skin, provides critical sensory feedback for grasping‐related tasks and perception of ecologically‐relevant stimuli. Despite its importance, studies of mechanoreceptors in primate hands are limited, in part due to challenges of sample availability and histological methods. Dermatoglyphs have been proposed as alternative proxies of mechanoreceptor density. We investigated the relationships between mechanoreceptors (Meissner and Pacinian corpuscles), dermatoglyphs, and demography in the apical finger pads of 15 juvenile to adult rhesus macaques (Macaca mulatta) from a free‐ranging population at Cayo Santiago Primate Field Station (Puerto Rico). Our results indicate substantial interindividual variation in mechanoreceptor density (Meissner corpuscles: 11.9–43.3 corpuscles/mm²; Pacinian corpuscles: 0–4.5 corpuscles/mm²). While sex and digit were generally not associated with variation, there was strong evidence of a developmental effect. Specifically, apical pad length, Meissner corpuscle size, and Pacinian corpuscle depth increased while mechanoreceptor densities decreased throughout juvenescence, suggesting that primate mechanoreceptors change as fingers grow during adolescence and then stabilize at physical maturity. We also found Meissner corpuscle density was significantly associated with dermatoglyph ridge width and spacing, such that density predicted by a dermatoglyph model was strongly correlated with observed values. Dermatoglyphs thus offer a useful proxy of relative Meissner corpuscle density in primates, which opens exciting avenues of noninvasive research. Finally, our results underscore the importance of considering demographic factors and methodology in comparative studies of primate touch. 

The existence of dark matter in the universe is inferred from abundant astrophysical and cosmological observations. The Global Argon Dark Matter Collaboration (GADMC) aims to perform the searches for dark matter in the form of weakly interacting massive particles (WIMPs), whose collisions with argon nuclei would produce nuclear recoils with tens of keV energy. Argon has been considered an excellent medium for the direct detection of WIMPs as argon-based scintillation detectors can make use of pulse shape discrimination (PSD) to separate WIMP-induced nuclear recoil signals from electron recoil backgrounds with extremely high efficiency. However, argon-based direct dark matter searches must confront the presence of intrinsic³⁹Ar as the predominant source of electron recoil backgrounds (it is a beta-emitter with an endpoint energy of 565 keV and half-life of 269 years). Even with PSD, the³⁹Ar activity in atmospheric argon (AAr), mainly produced and maintained by cosmic ray-induced nuclear reactions, limits the ultimate size of argon-based detectors and restricts their ability to probe very-low-energy events. The discovery of argon from deep underground wells with significantly less³⁹Ar than that in AAr was an important step in the development of direct dark matter detection experiments using argon as the active target. Thanks to pioneering research and successful R&D, in 2012, the first 160 kg batch of underground argon (UAr) was extracted from a CO₂well in Cortez, Colorado. The DarkSide-50 experiment at the Gran Sasso National Laboratory (LNGS) in Italy, the first liquid argon detector ever operated with a UAr target, demonstrated a ∼ 1,400 suppression of the³⁹Ar activity with respect to the atmospheric argon. An even larger suppression is expected for⁴²Ar (another intrinsic beta-emitter with the⁴²K daughter isotope, also a beta-emitter) as its production is expected mainly in the upper atmosphere. Following the results of DarkSide-50, the GADMC initiated the UAr project for extraction from underground and cryogenic purification of 100 t of argon to be used as a target in the next-generation experiment DarkSide-20k. This paper contains a description of the Urania Plant in Cortez, Colorado, where UAr is extracted; the Aria Plant in Sardinia, Italy, an industrial-scale plant comprising a 350-m state-of-the-art cryogenic isotopic distillation column, designed for further purification of the extracted argon and further reduction of the isotopic abundance of³⁹Ar; and DArT, a facility for UAr radiopurity qualification at the Canfranc Underground Laboratory (LSC), Spain. Moreover, the high radiopurity of UAr leads to other possible applications, for instance, for those neutrinoless double-beta decay experiments using argon as shielding material or, more generally, for all those activities on argon-based detectors in high-energy physics or nuclear physics, which will be briefly discussed. 

Machine learning models are updated as new data is acquired or new architectures are developed. These updates usually increase model performance, but may introduce backward compatibility errors, where individual users or groups of users see their performance on the updated model adversely affected. This problem can also be present when training datasets do not accurately reflect overall population demographics, with some groups having overall lower participation in the data collection process, posing a significant fairness concern. We analyze how ideas from distributional robustness and minimax fairness can aid backward compatibility in this scenario, and propose two methods to directly address this issue. Our theoretical analysis is backed by experimental results on CIFAR-10, CelebA, and Waterbirds, three standard image classification datasets. 

Abstract The growing frequency, intensity, and duration of extreme heat events necessitates interventions to reduce heat exposures. Local opportunities for heat adaptation may be optimally identified through collection of both quantitative exposure metrics and qualitative data on perceptions of heat. In this study, we used mixed methods to characterize heat exposure among urban residents in the area of Boston, Massachusetts, US, in summer 2020. Repeated interviews ofN = 24 study participants ascertained heat vulnerability and adaptation strategies. Participants also used low-cost sensors to collect temperature, location, sleep, and physical activity data. We saw significant differences across temperature metrics: median personal temperature exposures were 3.9 °C higher than median ambient weather station temperatures. Existing air conditioning (AC) units did not adequately control indoor temperatures to desired thermostat levels: even with AC use, indoor maximum temperatures increased by 0.24 °C per °C of maximum outdoor temperature. Sleep duration was not associated with indoor or outdoor temperature. On warmer days, we observed a range of changes in time-at-home, expected given our small study size. Interview results further indicated opportunities for heat adaptation interventions including AC upgrades, hydration education campaigns, and amelioration of energy costs during high heat periods. Our mixed methods design informs heat adaptation interventions tailored to the challenges faced by residents in the study area. The strength of our community-academic partnership was a large part of the success of the mixed methods approach. 

Abstract CUPID, the CUORE Upgrade with Particle Identification, is a next-generation experiment to search for neutrinoless double beta decay ($$0\mathrm {\nu \beta \beta }$$ $0\nu \beta \beta$) and other rare events using enriched Li$$_{2}$$ $_2^{}$$$^{100}$$ $_{}^{100}$MoO$$_{4}$$ $_4^{}$scintillating bolometers. It will be hosted by the CUORE cryostat located at the Laboratori Nazionali del Gran Sasso in Italy. The main physics goal of CUPID is to search for$$0\mathrm {\nu \beta \beta }$$ $0\nu \beta \beta$of$$^{100}$$ $_{}^{100}$Mo with a discovery sensitivity covering the full neutrino mass regime in the inverted ordering scenario, as well as the portion of the normal ordering regime with lightest neutrino mass larger than 10 meV. With a conservative background index of 10$$^{-4}$$ $_{}^{-4}$ cts$$/($$ $/($keV$$\cdot $$ $·$kg$$\cdot $$ $·$yr$$)$$ $)$, 240 kg isotope mass, 5 keV FWHM energy resolution at 3 MeV and 10 live-years of data taking, CUPID will have a 90% C.L. half-life exclusion sensitivity of$$1.8\cdot 10^{27}$$ $1.8·{10}^{27}$ yr, corresponding to an effective Majorana neutrino mass ($$m_{\beta \beta }$$ $m_{\beta \beta }$) sensitivity of 9–15 meV, and a$$3\sigma $$ $3\sigma$discovery sensitivity of$$1\cdot 10^{27}$$ $1·{10}^{27}$ yr, corresponding to an$$m_{\beta \beta }$$ $m_{\beta \beta }$range of 12–21 meV.