MMS SITL Ground Loop: Automating the Burst Data Selection Process.

Global-scale energy flow throughout Earth's magnetosphere is catalyzed by processes that occur at Earth's magnetopause (MP). Magnetic reconnection is one process responsible for solar wind entry into and global convection within the magnetosphere, and the MP location, orientation, and motion have an impact on the dynamics. Statistical studies that focus on these and other MP phenomena and characteristics inherently require MP identification in their event search criteria, a task that can be automated using machine learning so that more man hours can be spent on research and analysis. We introduce a Long-Short Term Memory (LSTM) Recurrent Neural Network model to detect MP crossings and assist studies of energy transfer into the magnetosphere. As its first application, the LSTM has been implemented into the operational data stream of the Magnetospheric Multiscale (MMS) mission. MMS focuses on the electron diffusion region of reconnection, where electron dynamics break magnetic field lines and plasma is energized. MMS employs automated burst triggers onboard the spacecraft and a Scientist-in-the-Loop (SITL) on the ground to select intervals likely to contain diffusion regions. Only low-resolution survey data is available to the SITL, which is insufficient to resolve electron dynamics. A strategy for the SITL, then, is to select all MP crossings. Of all 219 SITL selections classified as MP crossings during the first five months of model operations, the model predicted 166 (76%) of them, and of all 360 model predictions, 257 (71%) were selected by the SITL. Most predictions that were not classified as MP crossings by the SITL were still MP-like, in that the intervals contained mixed magnetosheath and magnetospheric plasmas. The LSTM model and its predictions are public to ease the burden of arduous event searches involving the MP, including those for EDRs. For MMS, this helps free up mission operation costs by consolidating manual classification processes into automated routines.

Energy partitioning constraints at kinetic scales in low-ß turbulence.

Turbulence is a fundamental physical process through which energy injected into a system at large scales cascades to smaller scales. In collisionless plasmas, turbulence provides a critical mechanism for dissipating electromagnetic energy. Here we present observations of plasma fluctuations in low-ß turbulence using data from NASA's Magnetospheric Multiscale mission in Earth's magnetosheath. We provide constraints on the partitioning of turbulent energy density in the fluid, ion-kinetic, and electron-kinetic ranges. Magnetic field fluctuations dominated the energy density spectrum throughout the fluid and ion-kinetic ranges, consistent with previous observations of turbulence in similar plasma regimes. However, at scales shorter than the electron inertial length, fluctuation power in electron kinetic energy significantly exceeded that of the magnetic field, resulting in an electron-motion-regulated cascade at small scales. This dominance should be highly relevant for the study of turbulence in highly magnetized laboratory and astrophysical plasmas.

Wave-particle energy exchange directly observed in a kinetic Alfvén-branch wave.

Alfvén waves are fundamental plasma wave modes that permeate the universe. At small kinetic scales, they provide a critical mechanism for the transfer of energy between electromagnetic fields and charged particles. These waves are important not only in planetary magnetospheres, heliospheres and astrophysical systems but also in laboratory plasma experiments and fusion reactors. Through measurement of charged particles and electromagnetic fields with NASA's Magnetospheric Multiscale (MMS) mission, we utilize Earth's magnetosphere as a plasma physics laboratory. Here we confirm the conservative energy exchange between the electromagnetic field fluctuations and the charged particles that comprise an undamped kinetic Alfvén wave. Electrons confined between adjacent wave peaks may have contributed to saturation of damping effects via nonlinear particle trapping. The investigation of these detailed wave dynamics has been unexplored territory in experimental plasma physics and is only recently enabled by high-resolution MMS observations.

Effect of gel structure on the dissolution of heat-induced beta-lactoglobulin gels in alkali.

The dissolution of heat-induced beta-lactoglobulin (betaLg) gels in alkaline solution plays an important role in the cleaning-in-place of fouled dairy and other food plants. The dissolution behavior is strongly influenced by the conditions under which the gel is formed. At low alkaline pH values (<13), the dissolution rate constant kg' decreases with longer gelation time and higher temperature. An inverse relationship is observed between the kg' value and the amount of covalently cross-linked proteins in the gel, which is mainly due to disulfide bonds. beta-Elimination kinetics of intramolecular cystines in betaLg have been used to estimate the amount of intermolecular disulfide bonds that are cleaved during dissolution. The results call into question current dissolution models for these systems based on external mass transfer through the fluid next to the swollen gel. At low temperatures, the amount of disulfide cleavage is estimated to be small, indicating that dissolution is likely to involve the (slow) disengagement of large protein clusters, analogous to the dissolution of synthetic polymers.

The pH threshold in the dissolution of beta-lactoglobulin gels and aggregates in alkali.

The existence of a practical minimum pH for the dissolution of heat-induced whey gels in alkaline solutions has been studied using beta-lactoglobulin (betaLg) as a model protein. A sharp transition in solubility was observed between pH 11 and 12; this transition shifts to higher pHs for gels formed at higher temperatures and for longer gelling times. The breakdown reactions of heat-induced aggregates in alkali were monitored with size exclusion chromatography. The destruction of large aggregates was faster at higher pH and also showed a transition between pH 11 and 12. Using tryptophan fluorescence and near- and far-UV circular dichroism, this transition was assigned to the base-induced denaturation observed in solutions of aggregates (pK 11.53). It is suggested that the high protein repulsion caused by the large number of charges at pH > 11.5 drives the unfolding of the protein and the disruption of the intermolecular noncovalent bonds. Concentrated urea and GuHCl were found to be less effective than a pH 12 solution in destroying large aggregates. Aggregates formed for a long time (80 degrees C for 24 h) contained a larger number of intermolecular disulfide bonds that hinder the dissolution process. Gels formed at low temperatures (65 degrees C for 60 min), with fewer intermolecular noncovalent bonds, showed a similar solubility-pH profile to that observed for the base-induced denaturation of unheated beta-lactoglobulin (betaLg) (pK 10.63).

Swelling and dissolution of beta-lactoglobulin gels in alkali.

It is well documented in the literature that during the dissolution of whey protein gels in alkali, the gels swell to a great extent. However, the relevance of the swelling step in the dissolution process of the protein gel remains unknown. In the present article we present a systematic study on the swelling of beta-lactoglobulin gels at different alkaline pH and ionic strengths. The equilibrium swelling degree at different conditions has been modeled using a simple model developed for polyelectrolyte gels, modified to take into account the ionization of the residues in a protein. The model can describe the swelling behavior of the gels over a wide range of conditions, but it underpredicts the equilibrium swelling under conditions close to those when dissolution is observed. Dissolution is only noticeable above pH 11.5-12 and only for those gels that are swollen over a minimum degree, suggesting the existence of a dissolution threshold.