Effective squirmer models for self-phoretic chemically active spherical colloids

Various aspects of self-motility of chemically active colloids in Newtonian fluids can be captured by simple models for their chemical activity plus a phoretic slip hydrodynamic boundary condition on their surface. For particles of simple shapes (e.g., spheres) -- as employed in many experimental studies -- which move at very low Reynolds numbers in an unbounded fluid, such models of chemically active particles effectively map onto the well studied so-called hydrodynamic squirmers [S. Michelin and E. Lauga, J. Fluid Mech. \textbf{747}, 572 (2014)]. Accordingly, intuitively appealing analogies of "pusher/puller/neutral" squirmers arise naturally. Within the framework of self-diffusiophoresis we illustrate the above mentioned mapping and the corresponding flows in an unbounded fluid for a number of choices of the activity function (i.e., the spatial distribution and the type of chemical reactions across the surface of the particle). We use the central collision of two active particles as a simple, paradigmatic case for demonstrating that in the presence of other particles or boundaries the behavior of chemically active colloids may be \textit{qualitatively} different, even in the far field, from the one exhibited by the corresponding "effective squirmer", obtained from the mapping in an unbounded fluid. This emphasizes that understanding the collective behavior and the dynamics under geometrical confinement of chemically active particles necessarily requires to explicitly account for the dependence of the hydrodynamic interactions on the distribution of chemical species resulting from the activity of the particles.Comment: 26 pages, 11 figure

Towards a single-molecule FRET study of Frauenfelder's nonexponential rebinding of CO in myoglobin

Early time-resolved experiments by Frauenfelder on the ensemble of the kinetic rebinding of CO to myoglobin molecules resulted in a stretched exponential relaxa-tion due to a very large spread of the reaction rates of individual molecules. These results were assigned to the heterogeneity in this system originated from different conformations of different single-molecule proteins and from the widely different re-action rates associated with each of these conformations. The work presented in this thesis contains two lines of research. On the one hand, we investigate the Förster Resonance Energy Transfer (FRET) of dye labeled-carboxymyoglobin (MbCO) in the ensemble to show the feasibility of performing single molecule-FRET experiments to study the kinetic rebinding of CO to myoglobin (Chapter 3,4). On the other hand, we study the Förster theory about a stretched-exponential fluorescence intensity decay under ensemble conditions for a distribution of acceptors in the vicinity of each donor; This non-exponential kinetics arise from a distribution of the exponential steps originated from different single molecules. Using single-molecule microscopy, we study the histograms of the decay rates of single fluorophore molecules (Azaoxa-triangulenium, ADOTA dye) as donor in the presence of acceptors (ATTO575Q dye) both doped in thin polymeric layers as exponential which average out as non-exponential decay in the ensemble (Chapter 5).NWOBiological and Soft Matter Physic

Handling Computation Hardness and Time Complexity Issue of Battery Energy Storage Scheduling in Microgrids by Deep Reinforcement Learning

With the development of microgrids (MGs), an energy management system (EMS) is required to ensure the stable and economically efficient operation of the MG system. In this paper, an intelligent EMS is proposed by exploiting the deep reinforcement learning (DRL) technique. DRL is employed as the effective method for handling the computation hardness of optimal scheduling of the charge/discharge of battery energy storage in the MG EMS. Since the optimal decision for charge/discharge of the battery depends on its state of charge given from the consecutive time steps, it demands a full-time horizon scheduling to obtain the optimum solution. This, however, increases the time complexity of the EMS and turns it into an NP-hard problem. By considering the energy storage system’s charging/discharging power as the control variable, the DRL agent is trained to investigate the best energy storage control method for both deterministic and stochastic weather scenarios. The efficiency of the strategy suggested in this study in minimizing the cost of purchasing energy is also shown from a quantitative perspective through programming verification and comparison with the results of mixed integer programming and the heuristic genetic algorithm (GA)

Glucocorticoids, master modulators of the thymic catecholaminergic system?

There is evidence that the major mediators of stress, i.e., catecholamines and glucocorticoids, play an important role in modulating thymopoiesis and consequently immune responses. Furthermore, there are data suggesting that glucocorticoids influence catecholamine action. Therefore, to assess the putative relevance of glucocorticoid-catecholamine interplay in the modulation of thymopoiesis we analyzed thymocyte differentiation/maturation in non-adrenalectomized and andrenalectomized rats subjected to treatment with propranolol (0.4 mg.100 g body weight(-1).day(-1)) for 4 days. The effects of beta-adrenoceptor blockade on thymopoiesis in non-adrenalectomized rats differed not only quantitatively but also qualitatively from those in adrenalectomized rats. In adrenalectomized rats, besides a more efficient thymopoiesis [judged by a more pronounced increase in the relative proportion of the most mature single-positive TCR alpha beta(high) thymocytes as revealed by two-way ANOVA; for CD4(+)CD8(-)F (1,20) = 10.92, P lt 0.01; for CD4(-)CD8(+)F (1,20) = 7.47, P lt 0.05], a skewed thymocyte maturation towards the CD4(-)CD8(+) phenotype, and consequently a diminished CD4(+)CD8(-)/CD4(-)CD8(+) mature TCR alpha beta(high) thymocyte ratio (3.41 +/- 0.21 in non-adrenalectomized rats vs 2.90 +/- 0.31 in adrenalectomized rats, P lt 0.05) were found. Therefore, we assumed that catecholaminergic modulation of thymopoiesis exhibits a substantial degree of glucocorticoid-dependent plasticity. Given that glucocorticoids, apart from catecholamine synthesis, influence adrenoceptor expression, we also hypothesized that the lack of adrenal glucocorticoids affected not only beta-adrenoceptor- but also alpha-adrenoceptor-mediated modulation of thymopoiesis

Ensemble Learning for Low-Level Hardware-Supported Malware Detection

Abstract. Recent work demonstrated hardware-based online malware detection using only low-level features. This detector is envisioned as a first line of defense that prioritizes the application of more expensive and more accurate software detectors. Critical to such a framework is the detection performance of the hardware detector. In this paper, we explore the use of both specialized detectors and ensemble learning tech-niques to improve performance of the hardware detector. The proposed detectors reduce the false positive rate by more than half compared to a single detector, while increasing the detection rate. We also contribute approximate metrics to quantify the detection overhead, and show that the proposed detectors achieve more than 11x reduction in overhead compared to a software only detector (1.87x compared to prior work), while improving detection time. Finally, we characterize the hardware complexity by extending an open core and synthesizing it on an FPGA platform, showing that the overhead is minimal.