Mesoscopic model for colloidal particles, powders and granular solids

A simulation model is presented, comprising elastic spheres with a short range attraction. Besides conservative forces, radial- and shear friction, and radial noise are added. The model can be used to simulate colloids, granular solids and powders, and the parameters may be related to experimental systems via the range of attraction and the adhesion energy. The model shares the simplicity and speed of Dissipative Particle Dynamics (DPD), yet the predictions are rather non-trivial. We demonstrate that the model predicts the correct scaling relations for fracture of granular solids, and we present a schematic phase diagram. This shows liquid-vapor coexistence for sufficiently large interaction range, with a surface tension that follows Ising criticality. For smaller interaction range only solid-vapor coexistence is found, but for very small attractive interaction range stable liquid-vapor coexistence reappears due to pathological stability of the solid phase. At very low temperature the model forms a glassy state.Comment: 12 pages, 6 figures, accepted by Physical Review E, typos correcte

Fine structure of proton-neutron mixed symmetry states in some N=80 isotones

A microscopic multiphonon approach is adopted to investigate the structure of some low-lying states observed experimentally in the N = 80 isotones 134Xe, 136Ba, and 138Ce. The calculation yields levels and electromagnetic transition strengths in good agreement with experiments and relates the observed selection rules to the neutron proton symmetry and phonon content of the observed states. Moreover, it ascribes the splitting of theM1 strength in 138Ce to the proton subshell closure which magnifies the role of pairing in the excitation mechanism

Current-voltage characteristic of parallel-plane ionization chamber with inhomogeneous ionization

The balances of particles and charges in the volume of parallel-plane ionization chamber are considered. Differential equations describing the distribution of current densities in the chamber volume are obtained. As a result of the differential equations solution an analytical form of the current-voltage characteristic of parallel-plane ionization chamber with inhomogeneous ionization in the volume is got.Comment: 8 pages, 4 figure

Cell shape recognition by colloidal cell imprints: Energy of the cell-imprint interaction

The results presented in this study are aimed at the theoretical estimate of the interactions between a spherical microbial cell and the colloidal cell imprints in terms of the Derjaguin, Landau, Vervey, and Overbeek (DLVO) surface forces. We adapted the Derjaguin approximation to take into account the geometry factor in the colloidal interaction between a spherical target particle and a hemispherical shell at two different orientations with respect to each other. We took into account only classical DLVO surface forces, i.e., the van der Waals and the electric double layer forces, in the interaction of a spherical target cell and a hemispherical shell as a function of their size ratio, mutual orientation, distance between their surfaces, their respective surface potentials, and the ionic strength of the aqueous solution. We found that the calculated interaction energies are several orders higher when match and recognition between the target cell and the target cell imprint is achieved. Our analysis revealed that the recognition effect of the hemispherical shell towards the target microsphere comes from the greatly increased surface contact area when a full match of their size and shape is produced. When the interaction between the surfaces of the hemishell and the target cell is attractive, the recognition greatly amplifies the attraction and this increases the likelihood of them to bind strongly. However, if the surface interaction between the cell and the imprint is repulsive, the shape and size match makes this interaction even more repulsive and thus decreases the likelihood of binding. These results show that the surface chemistry of the target cells and their colloidal imprints is very important in controlling the outcome of the interaction, while the shape recognition only amplifies the interaction. In the case of nonmonotonous surface-to-surface interaction we discovered some interesting interplay between the effects of shape match and surface chemistry which is discussed in the paper. The results from this study establish the theoretical basis of cell shape recognition by colloidal cell imprints which, combined with cell killing strategies, could lead to an alternative class of cell shape selective antimicrobials, antiviral, and potentially anticancer therapies

Deep Reinforcement Learning for Concentric Tube Robot Control with a Goal-Based Curriculum

Concentric Tube Robots (CTRs), a type of continuum robot, are a collection of concentric, pre-curved tubes composed of super elastic nickel titanium alloy. CTRs can bend and twist from the interactions between neighboring tubes causing the kinematics and therefore control of the end-effector to be very challenging to model. In this paper, we develop a control scheme for a CTR end-effector in Cartesian space with no prior kinematic model using a deep reinforcement learning (DRL) approach with a goal-based curriculum reward strategy. We explore the use of curricula by changing the goal tolerance through training with constant, linear and exponential decay functions. Also, relative and absolute joint representations as a way of improving training convergence are explored. Quantitative comparisons for combinations of curricula and joint representations are performed and the exponential decay relative approach is used for training a robust policy in a noise-induced simulation environment. Compared to a previous DRL approach, our new method reduces training time and employs a more complex simulation environment. We report mean Cartesian errors of 1.29 mm and a success rate of 0.93 with a relative decay curriculum. In path following, we report mean errors of 1.37 mm in a noise-induced path following task. Albeit in simulation, these results indicate the promise of using DRL in model free control of continuum robots and CTRs in particular

Spectral observations of X Persei: Connection between H-alpha and X-ray emission

We present spectroscopic observations of the Be/X-ray binary X Per obtained during the period 1999 - 2018. Using new and published data, we found that during "disc-rise" the expansion velocity of the circumstellar disc is 0.4 - 0.7 km/s. Our results suggest that the disc radius in recent decades show evidence of resonant truncation of the disc by resonances 10:1, 3:1, and 2:1, while the maximum disc size is larger than the Roche lobe of the primary and smaller than the closest approach of the neutron star. We find correlation between equivalent width of H-alpha emission line ($W\alpha$) and the X-ray flux, which is visible when $15 \: \AA \: < W\alpha \le 40 \: \AA$. The correlation is probably due to wind Roche lobe overflow.Comment: Accepted for publication in Astronomy & Astrophysic

Artificial intelligence and automation in endoscopy and surgery

Modern endoscopy relies on digital technology, from high-resolution imaging sensors and displays to electronics connecting configurable illumination and actuation systems for robotic articulation. In addition to enabling more effective diagnostic and therapeutic interventions, the digitization of the procedural toolset enables video data capture of the internal human anatomy at unprecedented levels. Interventional video data encapsulate functional and structural information about a patient’s anatomy as well as events, activity and action logs about the surgical process. This detailed but difficult-to-interpret record from endoscopic procedures can be linked to preoperative and postoperative records or patient imaging information. Rapid advances in artificial intelligence, especially in supervised deep learning, can utilize data from endoscopic procedures to develop systems for assisting procedures leading to computer-assisted interventions that can enable better navigation during procedures, automation of image interpretation and robotically assisted tool manipulation. In this Perspective, we summarize state-of-the-art artificial intelligence for computer-assisted interventions in gastroenterology and surgery