Prototype of running clinical trials in an untrustworthy environment using blockchain.

Monitoring and ensuring the integrity of data within the clinical trial process is currently not always feasible with the current research system. We propose a blockchain-based system to make data collected in the clinical trial process immutable, traceable, and potentially more trustworthy. We use raw data from a real completed clinical trial, simulate the trial onto a proof of concept web portal service, and test its resilience to data tampering. We also assess its prospects to provide a traceable and useful audit trail of trial data for regulators, and a flexible service for all members within the clinical trials network. We also improve the way adverse events are currently reported. In conclusion, we advocate that this service could offer an improvement in clinical trial data management, and could bolster trust in the clinical research process and the ease at which regulators can oversee trials

Integrating biomedical research and electronic health records to create knowledge-based biologically meaningful machine-readable embeddings.

In order to advance precision medicine, detailed clinical features ought to be described in a way that leverages current knowledge. Although data collected from biomedical research is expanding at an almost exponential rate, our ability to transform that information into patient care has not kept at pace. A major barrier preventing this transformation is that multi-dimensional data collection and analysis is usually carried out without much understanding of the underlying knowledge structure. Here, in an effort to bridge this gap, Electronic Health Records (EHRs) of individual patients are connected to a heterogeneous knowledge network called Scalable Precision Medicine Oriented Knowledge Engine (SPOKE). Then an unsupervised machine-learning algorithm creates Propagated SPOKE Entry Vectors (PSEVs) that encode the importance of each SPOKE node for any code in the EHRs. We argue that these results, alongside the natural integration of PSEVs into any EHR machine-learning platform, provide a key step toward precision medicine

Secondary terms in the number of vanishings of quadratic twists of elliptic curve L-functions

We examine the number of vanishings of quadratic twists of the L-function associated to an elliptic curve. Applying a conjecture for the full asymptotics of the moments of critical L-values we obtain a conjecture for the first two terms in the ratio of the number of vanishings of twists sorted according to arithmetic progressions.Comment: 16 pages, many figure

Wavelength conversion by cavity-enhanced injection-locked four-wavemixing in a fiber-Bragg-grating coupled diode laser

Four-wave mixing (FWM) in a fiber-Bragg-grating (FBG) coupled semiconductor laser is investigated. We show that a large resonance enhancement of the FWM conversion efficiency can be obtained when the laser cavity is injection-locked by the converted signal, and apply this technique to the wavelength conversion of 1-Gb/s modulated signals. Furthermore, we discuss how the spectral width of these resonances can be increased to make this approach suitable to higher bit rates

Folded-path self-pumped wavelength converter based on four-wave mixing in a semiconductor optical amplifier

A four-wave mixing wavelength converter with no external pump laser and very low input signal power requirements is characterized. The wavelength conversion occurs inside a high-reflection/antireflection coated semiconductor optical amplifier pigtailed with a fiber Bragg grating. The pump signal is provided by the lasing mode at the Bragg wavelength. A 1-mW optical signal modulated at 2.5 Gb/s is converted over 9 mm with error rates below 10^-9