EPJ Data Science Highlight - Twitter’s tampered samples: Limitations of big data sampling in social media
- Published on 16 January 2019
Social networks are widely used as sources of data in computational social science studies, and so it is of particular importance to determine whether these datasets are bias-free. In EPJ Data Science, Jürgen Pfeffer, Katja Mayer and Fred Morstatter demonstrate how Twitter’s sampling mechanism is prone to manipulation that could influence how researchers, journalists, marketeers and policy analysts interpret their data.
(Guest post by Jürgen Pfeffer, Katja Mayer and Fred Morstatter, originally published in the SpringerOpen blog)
- Published on 15 January 2019
A new study presents new models describing how the adsorption of calcium, barium and strontium ions onto biological membranes may affect the functions of cells
Ions with two positive electrical charges, such as calcium ions, play a key role in biological cell membranes. The adsorption of ions in solution onto the membrane surface is so significant that it affects the structural and functional properties of the biological cells. Specifically, ions interact with surface molecules such as a double layer of lipids, or liposomes, formed from phosphatidylcholines (PC). In a new study published in EPJ E, Izabela Dobrzyńska from the University of Białystok, Poland, develops a mathematical model describing the electrical properties of biological membranes when ions such as calcium, barium and strontium adsorb onto them at different pH levels. Her works helps shed light on how ion adsorption reduces the effective surface concentration of add-on molecules with a specific function that can take part in biochemical reactions. These factors need to be taken into account when studying the diverse phenomena that occur at the lipid membrane in living cells, such as ion transport mechanisms.
- Published on 11 January 2019
Lattice calculations using the framework of effective field theory have been applied to a wide range of few-body and many-body systems. One of the challenges of these calculations is to remove systematic errors arising from the nonzero lattice spacing. While the lattice improvement program pioneered by Symanzik provides a formalism for doing this and has already been utilized in lattice effective field theory calculations, the effectiveness of the improvement program has not been systematically benchmarked.
In this work lattice improvement is used to remove lattice errors for a one-dimensional system of bosons with zero-range interactions. To this aim the improved lattice action up to next-to-next-to-leading order is constructed and it is verified that the remaining errors scale as the fourth power of the lattice spacing for observables involving as many as five particles. These results provide a guide for increasing the accuracy of future calculations in lattice effective field theory with improved lattice actions.