Rheological response of a modified polyacrylamide-silica nanoparticles hybrid at high salinity and temperature.

Water-soluble polyacrylamides have often been used to modify flow response in various water-based technologies and industrial processes, including paints, water treatment, paper manufacturing, and chemical enhanced oil recovery. Polymers are susceptible to degradation at combined high salinity and elevated temperature conditions which limits their overall performance. Hybrid mixtures of hydrophobically modified polyacrylamide (HMPAM) with hydrophobically modified silica nanoparticles (NPs) emerged as a promising strategy for achieving enhanced stability and high viscosity in brines having a high total dissolved solids (TDS) content and high hardness at elevated temperatures (>20 wt% TDS, including >1.

Towards practical privacy-preserving genome-wide association study.

Background: The deployment of Genome-wide association studies (GWASs) requires genomic information of a large population to produce reliable results. This raises significant privacy concerns, making people hesitate to contribute their genetic information to such studies.

Results: We propose two provably secure solutions to address this challenge: (1) a somewhat homomorphic encryption (HE) approach, and (2) a secure multiparty computation (MPC) approach.

Privacy-preserving logistic regression training.

Background: Logistic regression is a popular technique used in machine learning to construct classification models. Since the construction of such models is based on computing with large datasets, it is an appealing idea to outsource this computation to a cloud service. The privacy-sensitive nature of the input data requires appropriate privacy preserving measures before outsourcing it.

Transgenic mice as a model of pre-clinical Alzheimer's disease.

At diagnosis, Alzheimer's disease (AD) brains are extensively burdened with plaques and tangles and display a degree of synaptic failure most likely beyond therapeutic treatment. It is therefore crucial to identify early pathological events in the progression of the disease. While it is not currently feasible to identify and study early, pre-clinical stages of AD, transgenic (Tg) models offer a valuable tool in this regard.