Acute kidney injury in the elderly: predisposition to chronic kidney disease and vice versa.

There have been considerable advances in the past few years in our understanding of how chronic kidney disease (CKD) predisposes to acute kidney injury (AKI) and vice versa. This review shows, however, that few studies have focused on the elderly or conducted stratified analysis by age. It does appear that elderly patients with estimated glomerular filtration rate (eGFR) 45-59 ml/min/1.73 m(2) are at higher risk for AKI compared with their counterparts with eGFR >60 ml/min/1.73 m(2). This is a similar relationship to that seen in younger patients, although effect size appears smaller. As the incidence of AKI has been increasing over the past several years, the proportion of elderly patients surviving after AKI has also been increasing. Since AKI heightens the risk for the development and acceleration of CKD, this implies significant public health concerns with regard to the absolute number of elderly persons developing incident CKD

Optimization of sharp and viewing-angle-independent structural color

Structural coloration produces some of the most brilliant colors in nature and has many applications. However, the two competing properties of narrow bandwidth and broad viewing angle have not been achieved simultaneously in previous studies. Here, we use numerical optimization to discover geometries where a sharp 7% bandwidth in scattering is achieved, yet the peak wavelength varies less than 1%, and the peak height and peak width vary less than 6% over broad viewing angles (0--90$^\circ$) under a directional illumination. Our model system consists of dipole scatterers arranged into several rings; interference among the scattered waves is optimized to yield the wavelength-selective and angle-insensitive response. Such designs can be useful for the recently proposed transparent displays that are based on wavelength-selective scattering

Private Matchings and Allocations

We consider a private variant of the classical allocation problem: given k goods and n agents with individual, private valuation functions over bundles of goods, how can we partition the goods amongst the agents to maximize social welfare? An important special case is when each agent desires at most one good, and specifies her (private) value for each good: in this case, the problem is exactly the maximum-weight matching problem in a bipartite graph. Private matching and allocation problems have not been considered in the differential privacy literature, and for good reason: they are plainly impossible to solve under differential privacy. Informally, the allocation must match agents to their preferred goods in order to maximize social welfare, but this preference is exactly what agents wish to hide. Therefore, we consider the problem under the relaxed constraint of joint differential privacy: for any agent i, no coalition of agents excluding i should be able to learn about the valuation function of agent i. In this setting, the full allocation is no longer published---instead, each agent is told what good to get. We first show that with a small number of identical copies of each good, it is possible to efficiently and accurately solve the maximum weight matching problem while guaranteeing joint differential privacy. We then consider the more general allocation problem, when bidder valuations satisfy the gross substitutes condition. Finally, we prove that the allocation problem cannot be solved to non-trivial accuracy under joint differential privacy without requiring multiple copies of each type of good.Comment: Journal version published in SIAM Journal on Computation; an extended abstract appeared in STOC 201

The Right and the Good: Distributive Justice and Neural Encoding of Equity and Efficiency

Distributive justice concerns how individuals and societies distribute benefits and burdens in a just or moral manner. We combined distribution choices with functional magnetic resonance imaging to investigate the central problem of distributive justice: the trade-off between equity and efficiency. We found that the putamen responds to efficiency, whereas the insula encodes inequity, and the caudate/septal subgenual region encodes a unified measure of efficiency and inequity (utility). Notably, individual differences in inequity aversion correlate with activity in inequity and utility regions. Against utilitarianism, our results support the deontological intuition that a sense of fairness is fundamental to distributive justice but, as suggested by moral sentimentalists, is rooted in emotional processing. More generally, emotional responses related to norm violations may underlie individual differences in equity considerations and adherence to ethical rules

Systematic method for thermomechanically consistent coarse graining: a universal model for methacrylate-based polymers

We present a versatile systematic two-bead-per-monomer coarse-grain modeling strategy for simulating the -thermomechanical behavior of methacrylate polymers at length and time scales far exceeding atomistic -simulations. We establish generic bonded interaction parameters via Boltzmann inversion of probability distributions obtained from the common coarse-grain bead center locations of five different methacrylate polymers. Distinguishing features of each monomer side-chain group are captured using Lennard-Jones nonbonded potentials with -parameters specified to match the density and glass-transition temperature values obtained from all-atomistic simulations. The developed force field is validated using Flory–Fox scaling relationships, self-diffusion coefficients of -monomers, and modulus of elasticity for p (MMA). Our approach establishes a transferable, efficient, and accurate scale--bridging strategy for investigating the thermomechanics of copolymers, polymer blends, and nanocomposites

Conversion detection for improved online ad selection

Online ads sometimes continue unchanged even after the ad had resulted in a conversion, e.g., after a user has purchased the advertised product. Many users find such continued presence of the ad annoying. Also, not refreshing the ad with a different product represents lost revenue for the website publisher and the ad network. This disclosure describes techniques to detect if the user has purchased a given product by analyzing, with user consent and permission, user data such as emails and other data. Upon detecting conversion, display of ads relating to the product or similar products is discontinued

Fourier Neural Operator Networks: A Fast and General Solver for the Photoacoustic Wave Equation

Simulation tools for photoacoustic wave propagation have played a key role in advancing photoacoustic imaging by providing quantitative and qualitative insights into parameters affecting image quality. Classical methods for numerically solving the photoacoustic wave equation relies on a fine discretization of space and can become computationally expensive for large computational grids. In this work, we apply Fourier Neural Operator (FNO) networks as a fast data-driven deep learning method for solving the 2D photoacoustic wave equation in a homogeneous medium. Comparisons between the FNO network and pseudo-spectral time domain approach demonstrated that the FNO network generated comparable simulations with small errors and was several orders of magnitude faster. Moreover, the FNO network was generalizable and can generate simulations not observed in the training data