- Published on 17 March 2021
By considering how some bacteria will swim faster within higher nutrient concentrations, researchers have created a more accurate model of how these microbes search for nutrients
Many bacteria swim towards nutrients by rotating the helix-shaped flagella attached to their bodies. As they move, the cells can either ‘run’ in a straight line, or ‘tumble’ by varying the rotational directions of their flagella, causing their paths to randomly change course. Through a process named ‘chemotaxis,’ bacteria can decrease their rate of tumbling at higher concentrations of nutrients, while maintaining their swimming speeds. In more hospitable environments like the gut, this helps them to seek out nutrients more easily. However, in more nutrient-sparse environments, some species of bacteria will also perform ‘chemokinesis’: increasing their swim speeds as nutrient concentrations increase, without changing their tumbling rates. Through new research published in EPJ E, Theresa Jakuszeit and a team at the University of Cambridge led by Ottavio Croze produced a model which accurately accounts for the combined influences of these two motions.
- Published on 04 March 2021
Models of galactic rotation curves built of a general relativistic framework could use gravitomagnetism to explain the effects of dark matter.
Observations of galactic rotation curves give one of the strongest lines of evidence pointing towards the existence of dark matter, a non-baryonic form of matter that makes up an estimated 85% of the matter in the observable Universe. Current assessments of galactic rotation curves are based upon a framework of Newtonian accounts of gravity, a new paper published in EPJ C, by Gerson Otto Ludwig, National Institute for Space Research, Brazil, suggests that if this is substituted with a general relativity-based model, the need to recourse to dark matter is relieved, replaced by the effects of gravitomagnetism.
EPJ B Highlight - Considering disorder and cooperative effects in photon escape rates from atomic gases
- Published on 26 February 2021
Investigating more complex models of photon escape rates from cold atomic gases could help researchers learn more about light-matter interactions.
Whilst a great deal of research has studied the rates of photons escaping from cold atomic gases, these studies have used a scalar description of light leaving some of its properties untested. In a new paper published in EPJ B Louis Bellando, a post-doctoral researcher at LOMA, University of Bordeaux, France, and his coauthors—Aharon Gero and Eric Akkermans, Technion-Israel Institute of Technology, Israel, and Robin Kaiser, Université Côte d'Azur, France—aim to numerically investigative the roles of cooperative effects and disorder in photon escape rates from a cold atomic gas to construct a model that considers the vectorial nature of light. Thus, the study accounts for properties of light, previously neglected.
- Published on 19 February 2021
By using a more complex model for neutron scattering data, researchers can better understand the composition of materials such as milk.
Neutron scattering is a technique commonly used in physics and biology to understand the composition of complex multicomponent mixtures and is increasingly being used to study applied materials such as food. A new paper published in EPJ E by Gregory N Smith, Niels Bohr Institute, University of Copenhagen, Denmark, shows an example of neutron scattering in the area of food science. Smith uses neutron scattering to better investigate casein micelles in milk, with the aim of developing an approach for future research.
Smith, also a researcher at the ISIS Neutron and Muon Source in the UK, explains why better modelling of how neutrons are scattered by structures in colloid materials is important. “How well you can understand the structure of a system from scattering data depends on how good your model is, and the better and more realistic your model, the better your understanding,” the researcher says. “This is true for food as for any material. A better understanding of the structure of casein in milk can help better understand dairy products.”
- Published on 19 February 2021
Astrophysical and lab-created plasmas under the influence of magnetic fields are the source of intense study. New research seeks to understand the dynamics of position waves travelling through these clouds of highly ionised gas.
The investigation of Electron-Positron-Ion (EPI) plasma — a fully ionised gas of electrons and positrons that includes astrophysical plasmas like solar winds — has attracted a great deal of attention over the last twenty years. A new study published in EPJ D by Garston Tiofack, Faculty of Sciences, University of Marousa, Cameroon, and colleagues, assesses the dynamics of positron acoustic waves (PAWS) in EPI plasmas whilst under the influence of magnetic fields, or magnetoplasmas.
- Published on 09 February 2021
Researchers have used cosmological data to place stringent new limits on a model which emerges in attempts to reconcile gravity with the principles of quantum mechanics.
A description of gravity compatible with the principles of quantum mechanics has long been a widely pursued goal in physics. Existing theories of this ‘quantum gravity’ often involve mathematical corrections to Heisenberg’s Uncertainty Principle (HUP), which quantifies the inherent limits in the accuracy of any quantum measurement. These corrections arise when gravitational interactions are considered, leading to a ‘Generalized Uncertainty Principle’ (GUP). Two specific GUP models are often used: the first modifies the HUP with a linear correction, while the second introduces a quadratic one. Through new research published in EPJ C, Serena Giardino and Vincenzo Salzano at the University of Szczecin in Poland have used well-established cosmological observations to place tighter constraints on the quadratic model, while discrediting the linear model.
- Published on 02 February 2021
Novel approaches in graph theory have enabled researchers to reveal the characteristic configurations of neurons which arise as our brains process pain
The many different sensations our bodies experience are accompanied by deeply complex exchanges of information within the brain, and the feeling of pain is no exception. So far, research has shown how pain intensity can be directly related to specific patterns of oscillation in brain activity, which are altered by the activation and deactivation of the ‘interneurons’ connecting different regions of the brain. However, it remains unclear how the process is affected by ‘inhibitory’ interneurons, which prevent chemical messages from passing between these regions. Through new research published in EPJ B, researchers led by Fernando Montani at Instituto de Física La Plata, Argentina, show that inhibitory interneurons make up 20% of the circuitry in the brain required for pain processing.
- Published on 01 February 2021
A detailed analysis of theories which approximate the underlying properties of physical systems could lead to new advances in studies of low-energy nuclear processes
Over the past century, a wide variety of models have emerged to explain the complex behaviours which unfold within atomic nuclei at low energies. However, these theories bring up deep philosophical questions regarding their scientific value. Indeed, traditional epistemological tools have been rather elaborated to account for a unified and stabilised theory rather than to apprehend a plurality of models. Ideally, a theory is meant to be reductionist, unifying and fundamentalist. In view of the intrinsic limited precision of their prediction and of the difficulty in assessing a priori their range of applicability, as well as of their specific and disconnected character, traditional nuclear models are necessarily deficient when analysed by means of standard epistemological interpretative frameworks.
- Published on 29 January 2021
Building on previous studies of muon tomography techniques, this topical issue demonstrates a full-scale prototype for the technology, capable of determining the position of a small lead block within a large sensing area
Each year, billions of tons of goods are transported globally using cargo containers. Currently, there are concerns that this immense volume of traffic could be exploited to transport illicit nuclear materials, with little chance of detection. One promising approach to combating this issue is to measure how goods interact with charged particles named muons – which form naturally as cosmic rays interact with Earth’s atmosphere. Studies worldwide have now explored how this technique, named ‘muon tomography,’ can be achieved through a variety of detection technologies and reconstruction algorithms. In this article of EPJ Plus, a team headed by Francesco Riggi at the University of Catania, Italy, build on these results to develop a full-scale muon tomograph prototype.
- Published on 29 January 2021
Microscopically very different physical, biological and cultural systems all evolve through a sequence of stages, each characterized by stationary fluctuations around constant values of relevant macroscopic observables. Sudden and rapid changes, called quakes, induce transitions from one stage to the next and reveal the non-equilibrium nature of the dynamics. The duration of the stages increases over time, producing a multi-scaled dynamical behavior known in physics under the name of ``physical aging'', and rooted in all cases in a hierarchically structured underlying configuration space. Record Dynamics (RD) is a coarse-graining approach treating the staged evolution of complex metastable systems with the same statistical tools. This colloquium paper reviews RD methods and ideas that have gradually evolved over time and shows how RD can be applied to selected cases of biological and physical origin. The main property described is that quakes are a log-Poisson process and that the coarse-grained dynamics is therefore log-time homogeneous. The bibliography points the interested reader to the original RD papers and their background.