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Abstract One major challenge to scaling quantum dot qubits is the dense wiring requirements, making it difficult to envision fabricating large 2D arrays of nearest-neighbor-coupled qubits necessary for error correction. We describe a method to ameliorate this issue by spacing out the qubits using superconducting resonators facilitated by 3D integration. To prove the viability of this approach, we use integration to couple an off-chip high-impedance TiN resonator to a double quantum dot in a Si/SiGe heterostructure. Using the resonator as a dispersive gate sensor, we tune the device down to the single electron regime with an SNR = 5.36. Characterizing the individual systems shows 3D integration can be done while maintaining low-charge noise for the quantum dots and high-quality factors for the superconducting resonator (single photon Q L = 2.14 × 104 with Q i ≈ 3 × 105), necessary for readout and high-fidelity two-qubit gates.

Density matrix exponentiation (DME) is a general technique for using a quantum state ρ to enact the quantum operation e^{-iρθ} on a target system. It was first proposed in the context of quantum machine learning, but has since been shown to have broad applications in quantum metrology and computation. No experimental demonstration of DME has been performed thus far due to its demanding circuit depths and the need to efficiently generate multiple identical copies of ρ during the finite lifetime of the target system. In this work, we describe the first demonstration of the DME algorithm, which we accomplish using a superconducting quantum processor. Our demonstration relies on a 99.7% fidelity controlled-phase gate implemented using two tunable superconducting transmon qubits. We achieve a fidelity surpassing 90% at circuit depths exceeding 70 when comparing the output of the circuit executed on our quantum processor to a simulation assuming perfect operations and measurements.

Improving the built environment (BE) is viewed as one strategy to improve community diets and health. The present goal is to review the literature on the effects of BE on health, highlight its limitations, and explore the growing use of natural experiments in BE research, such as the advent of new supermarkets, revitalized parks, or new transportation systems. Based on recent studies on movers, a paradigm shift in built-environment health research may be imminent. Following the classic Moving to Opportunity study in the US, the present Moving to Health (M2H) strategy takes advantage of the fact that changing residential location can entail overnight changes in multiple BE variables. The necessary conditions for applying the M2H strategy to Geographic Information Systems (GIS) databases and to large longitudinal cohorts are outlined below. Also outlined are significant limitations of this approach, including the use of electronic medical records in lieu of survey data. The key research question is whether documented changes in BE exposure can be linked to changes in health outcomes in a causal manner. The use of geo-localized clinical information from regional health care systems should permit new insights into the social and environmental determinants of health. Keywords: Built environment (BE), Geographic information systems (GIS), Electronic medical records, Natural experiments, Obesity, Diabetes, Residential mobility

Rice Hull Ash (RHA) was converted to amorphous silica gel using a modified version of published literature procedures. The gels were characterized by a comparison of their CPMAS [29] Si NMR and Scanning Electron Microscopy (SEM) images with commercial silica gels. The resulting gels were silanized with a 7.5:1 mixture of methyltrichlorosilane and chloropropyltrichlorosilane and then reacted with poly(allylamine) (PAA) to produce the silica polyamine composite (SPC) BP-1. The BP-1 was then further modified with pyridine-2-carboxaldehyde to form the copper selective SPC, CuSELECT. This procedure follows that used to produce the commercialized version of these composite materials from commercially available amorphous silica gels. The composites were characterized by solid state NMR techniques, elemental analysis, SEM, porosimetry, and metal ion capacity and selectivity. The overall goal of the project was to determine the feasibility of using RHA to make SPC. The observed strengths and weaknesses of this approach are discussed.

Abstract Iron stable isotopes (δ56Fe) are a useful tool for studying Earth processes, many of which involve redox transformations between Fe(III) and Fe(II). Here, we present two related experimental efforts, a study of the kinetic isotope effects (KIEs) associated with the reduction of Fe(III)‐ethylenediaminetetraacetic acid (EDTA) to Fe(II), and measurements of the biological fractionation of Fe isotopes by phytoplankton in culture. Reductants tested were ascorbate, hydroxylamine, Mn(II), dithionite, and photoreduction at pH between 5 and 9 and temperatures from 0 to 100°C. Isotope fractionations were very large, and included both normal and inverse KIEs, ranging from −4‰ to +5‰. Experiments were reproducible, yielding similar results for triplicate experiments run concurrently and for experiments run weeks apart. However, fractionations were not predictable, without a clear relationship to reaction rate, temperature, pH, or the reductant used. Acquisition of Fe by eukaryotic phytoplankton also often involves the reduction of Fe(III) to Fe(II). Several species of diatoms and a coccolithophore were tested for Fe isotope fractionation in culture using EDTA, NTA, and DFB as Fe(III) chelating ligands, yielding fractionations from −1.3‰ to +0.6‰. Biological isotope effects were also unpredictable, showing no clear relationship to species, growth rate, or Fe concentration. Variability in Fe isotope fractionation observed in culture may be explained in part by the sensitivity of KIEs. This work has implications for the industrial purification of isotopes, interpretation of natural δ56Fe, and the use of Fe isotopes as a tracer Fe source and biological processes in the ocean and other natural systems.

Background Women with chronic coronary disease are generally older than men and have more comorbidities but less atherosclerosis. We explored sex differences in revascularization, guideline‐directed medical therapy, and outcomes among patients with chronic coronary disease with ischemia on stress testing, with and without invasive management. Methods and Results The ISCHEMIA (International Study of Comparative Health Effectiveness with Medical and Invasive Approaches) trial randomized patients with moderate or severe ischemia to invasive management with angiography, revascularization, and guideline‐directed medical therapy, or initial conservative management with guideline‐directed medical therapy alone. We evaluated the primary outcome (cardiovascular death, myocardial infarction, or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest) and other end points, by sex, in 1168 (22.6%) women and 4011 (77.4%) men. Invasive group catheterization rates were similar, with less revascularization among women (73.4% of invasive‐assigned women revascularized versus 81.2% of invasive‐assigned men; P

Some anterior chambers do not readily shallow because of insufficient posterior pressure and/or very deep anterior chamber anatomy, which can make unscrolling descemet membrane endothelial keratoplasty (DMEK) tissue more challenging with an unmodified tap technique. We present a hands-free method for augmenting posterior pressure by temporarily tucking cellulose sponges under the blades of the eyelid speculum. The sponges transfer some of the eyelid speculum’s weight onto the bulbar surface posterior to the iris, thereby indenting the sclera and causing the iris diaphragm to bulge further forward. This hands-free technique can transform a potentially challenging DMEK case into a more straightforward one by facilitating both a shallow anterior chamber and a bimanual unscrolling technique. However, it only works in bicameral eyes with a vitreous body (e.g., an eye with penetrating keratoplasty, vitreous syneresis, and axial myopia) and will not work in unicameral eyes after vitrectomy (e.g., an eye with an Anterior Chamber Intraocular Lens (ACIOL)).

Cognition and attention arise from the adaptive coordination of neural systems in response to external and internal demands. The low-dimensional latent subspace that underlies large-scale neural dynamics and the relationships of these dynamics to cognitive and attentional states, however, are unknown. We conducted functional magnetic resonance imaging as human participants performed attention tasks, watched comedy sitcom episodes and an educational documentary, and rested. Whole-brain dynamics traversed a common set of latent states that spanned canonical gradients of functional brain organization, with global desynchronization among functional networks modulating state transitions. Neural state dynamics were synchronized across people during engaging movie watching and aligned to narrative event structures. Neural state dynamics reflected attention fluctuations such that different states indicated engaged attention in task and naturalistic contexts, whereas a common state indicated attention lapses in both contexts. Together, these results demonstrate that traversals along large-scale gradients of human brain organization reflect cognitive and attentional dynamics.

Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9- to 11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM model predicted WM performance both across and within children-and captured individual differences in later recognition memory-but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed 2 network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in each age group differently. Thus, functional connectivity (FC) predicts SA and WM in youth, with networks predicting WM performance differing more between youths and adults than those predicting SA.

Resting-state functional connectivity (rsFC) measured with fMRI has been used to characterize functional brain maturation in typically and atypically developing children and adults. However, its reliability and utility for predicting development in infants and toddlers is less well understood. Here, we use fMRI data from the Baby Connectome Project study to measure the reliability and uniqueness of rsFC in infants and toddlers and predict age in this sample (8-to-26 months old; n = 170). We observed medium reliability for within-session infant rsFC in our sample, and found that individual infant and toddler’s connectomes were sufficiently distinct for successful functional connectome fingerprinting. Next, we trained and tested support vector regression models to predict age-at-scan with rsFC. Models successfully predicted novel infants’ age within ± 3.6 months error and a prediction R2 = .51. To characterize the anatomy of predictive networks, we grouped connections into 11 infant-specific resting-state functional networks defined in a data-driven manner. We found that connections between regions of the same network—i.e. within-network connections—predicted age significantly better than between-network connections. Looking ahead, these findings can help characterize changes in functional brain organization in infancy and toddlerhood and inform work predicting developmental outcome measures in this age range.

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback is a non-invasive, non-pharmacological therapeutic tool that may be useful for training behavior and alleviating clinical symptoms. Although previous work has used rt-fMRI to target brain activity in or functional connectivity between a small number of brain regions, there is growing evidence that symptoms and behavior emerge from interactions between a number of distinct brain areas. Here, we propose a new method for rt-fMRI, connectome-based neurofeedback, in which intermittent feedback is based on the strength of complex functional networks spanning hundreds of regions and thousands of functional connections. We first demonstrate the technical feasibility of calculating whole-brain functional connectivity in real-time and provide resources for implementing connectome-based neurofeedback. We next show that this approach can be used to provide accurate feedback about the strength of a previously defined connectome-based model of sustained attention, the saCPM, during task performance. Although, in our initial pilot sample, neurofeedback based on saCPM strength did not improve performance on out-of-scanner attention tasks, future work characterizing effects of network target, training duration, and amount of feedback on the efficacy of rt-fMRI can inform experimental or clinical trial designs.