Development and Validation of a Deep-Learning-Based Algorithm for Detecting and Classifying Metallic Implants in Abdominal and Spinal CT Topograms.

Purpose: To develop and validate a deep-learning-based algorithm (DLA) that is designed to segment and classify metallic objects in topograms of abdominal and spinal CT.

Methods: DLA training for implant segmentation and classification was based on a U-net-like architecture with 263 annotated hip implant topograms and 2127 annotated spine implant topograms. The trained DLA was validated with internal and external datasets.

Evaluating the employment effects of environmental regulation without abatement cost data: A nonparametric cost function approach.

Environmental policymakers are concerned that environmental regulations reduce employment. A microeconomic analysis illustrates that environmental regulations have an uncertain effect on employment, making this an empirical question. A standard cost function model, used in the literature, requires a lot of data such as pollution abatement cost data to examine effects of environmental regulations on employment, but such survey data is not always available.

UV cross-linked smart microgel membranes as free-standing diffusion barriers and nanoparticle bearing catalytic films.

In this study we use poly(-isopropylacrylamide) (PNIPAM) based copolymer microgels to create free-standing, transferable, thermoresponsive membranes. The microgels are synthesized by copolymerization of NIPAM with 2-hydroxy-4-(methacryloyloxy)-benzophenone (HMABP) and spin-coated on Si wafers. After subsequent cross-linking by UV-irradiation, the formed layers easily detach from the supporting material.

Reconstructing Nonparametric Productivity Networks.

Network models provide a general representation of inter-connected system dynamics. This ability to connect systems has led to a proliferation of network models for economic productivity analysis, primarily estimated non-parametrically using Data Envelopment Analysis (DEA). While network DEA models can be used to measure system performance, they lack a statistical framework for inference, due in part to the complex structure of network processes.

Influence of Li-Salt on the Mesophases of Pluronic Block Copolymers in Ionic Liquid.

We study the complex mixture of a polyethylene oxide--polypropylene oxide--polyethylene oxide triblock copolymer (Pluronic F127) with ionic liquid (IL) and Li-salt, which is potentially interesting as an electrolyte system with decoupled mechanical and ion-transport properties. Small-angle X-ray scattering (SAXS) and differential scanning calorimetry (DSC) are employed to scrutinize the phase structures and elucidate the ternary phase diagram. These data are combined with the ion diffusivities obtained by pulsed field gradient (PFG) nuclear magnetic resonance (NMR).