Multidimensional Demographic Analyses of COVID-19 Vaccine Inequality in the United States: A Systematic Review.

Background: COVID-19 vaccination uptake is associated with demographic characteristics such as age, sex, and ethnicity-race in the United States (U.S.).

Multivariate patterns among multimodal neuroimaging and clinical, cognitive, and daily functioning characteristics in bipolar disorder.

Individuals with bipolar disorder (BD) show heterogeneity in clinical, cognitive, and daily functioning characteristics, which challenges accurate diagnostics and optimal treatment. A key goal is to identify brain-based biomarkers that inform patient stratification and serve as treatment targets. The objective of the present study was to apply a data-driven, multivariate approach to quantify the relationship between multimodal imaging features and behavioral phenotypes in BD.

Estimating the Risk of Cardiovascular Events in U.S. Veterans Using the SMART Risk Score.

Background: Estimation of long-term risk for cardiovascular events using the SMART (Secondary Manifestations of Arterial Disease) risk score can be potentially valuable in devising risk mitigation strategies.

Objectives: The objective of this study was to apply the SMART risk score to compute the risk for major adverse cardiovascular events (MACE) in the U.S.

TOPS-speed complex-valued convolutional accelerator for feature extraction and inference.

Complex-valued neural networks process both amplitude and phase information, in contrast to conventional artificial neural networks, achieving additive capabilities in recognizing phase-sensitive data inherent in wave-related phenomena. The ever-increasing data capacity and network scale place substantial demands on underlying computing hardware. In parallel with the successes and extensive efforts made in electronics, optical neuromorphic hardware is promising to achieve ultra-high computing performances due to its inherent analog architecture and wide bandwidth.

Quantum key distribution implemented with d-level time-bin entangled photons.

High-dimensional photon states (qudits) are pivotal to enhance the information capacity, noise robustness, and data rates of quantum communications. Time-bin entangled qudits are promising candidates for implementing high-dimensional quantum communications over optical fiber networks with processing rates approaching those of classical telecommunications. However, their use is hindered by phase instability, timing inaccuracy, and low scalability of interferometric schemes needed for time-bin processing.