Self calibration iso-pathlength point in cylindrical tissue geometry: Solution of steady-state photon diffusion based on the extrapolated zero-boundary

Near-infrared optical techniques permit tissue diagnosis by surface measurement. However, the geometrical shape of this interface profiles the intensity of the surface measurement, which is found to have an iso-pathlength (IPL) point allowing for absorption identification independent of tissue scattering. The IPL point was projected in Monte Carlo (MC) simulation, validated experimentally in cylindrical tissues, but remains under-appreciated through analytical approaches. In this work, we present an analytical solution of an IPL point for steady-state diffusion based on the extrapolated zero-boundary condition. The same IPL points were found when comparing this solution to 3-D MC simulations for a tissue radius range of 5-8mm.Electrical and Computer Engineerin

Multi-stage phase retrieval algorithm based upon the gyrator transform

The gyrator transform is a useful tool for optical information processing applications. In this work we propose a multi-stage phase retrieval approach based on this operation as well as on the well-known Gerchberg-Saxton algorithm. It results in an iterative algorithm able to retrieve the phase information using several measurements of the gyrator transform power spectrum. The viability and performance of the proposed algorithm is demonstrated by means of several numerical simulations and experimental results

How synchronized human networks escape local minima

Finding the global minimum in complex networks while avoiding local minima is challenging in many types of networks. We study the dynamics of complex human networks and observed that humans have different methods to avoid local minima than other networks. Humans can change the coupling strength between them or change their tempo. This leads to different dynamics than other networks and makes human networks more robust and better resilient against perturbations. We observed high-order vortex states, oscillation death, and amplitude death, due to the unique dynamics of the network. This research may have implications in politics, economics, pandemic control, decision-making, and predicting the dynamics of networks with artificial intelligence.Comment: 13 pages, 5 figure

Synchronization of complex human networks

The synchronization of human networks is essential for our civilization, and understanding the motivations, behavior, and basic parameters that govern the dynamics of human networks is important in many aspects of our lives. Human ensembles have been investigated in recent years, but with very limited control over the network parameters and in noisy environments. In particular, research has focused predominantly on all-to-all coupling, whereas current social networks and human interactions are often based on complex coupling configurations, such as nearest-neighbor coupling and small-world networks. Because the synchronization of any ensemble is governed by its network parameters, studying different types of human networks while controlling the coupling and the delay is essential for understanding the dynamics of different types of human networks. We studied the synchronization between professional violin players in complex networks with full control over the network connectivity, coupling strength of each connection, and delay. We found that the usual models for coupled networks, such as the Kuramoto model, cannot be applied to human networks. We found that the players can change their periodicity by a factor of three to find a stable solution to the coupled network, or they can delete connections by ignoring frustrating signals. These additional degrees of freedom enable new strategies and yield better solutions than are possible within current models. Our results may influence numerous fields, including traffic management, epidemic control, and stock market dynamics.Comment: 9 pages, 7 figures, to be submitte

Ultrafast rogue wave patterns in fiber lasers

Fiber lasers are convenient for studying extreme and rare events, such as rogue waves, thanks to the lasers’ fast dynamics. Indeed, several types of rogue wave patterns were observed in fiber lasers at different time-scales: single peak, twin peak, and triple peak. We measured the statistics of these ultrafast rogue wave patterns with a time lens and developed a numerical model proving that the patterns of the ultrafast rogue waves were generated by the non-instantaneous relaxation of the saturable absorber together with the polarization mode dispersion of the cavity. Our results indicate that the dynamics of the saturable absorber is directly related to the dynamics of ultrafast extreme events in lasers

The picosecond structure of ultra-fast rogue waves

We investigated ultrafast rogue waves in fiber lasers and found three different patterns of rogue waves: single- peaks, twin-peaks, and triple-peaks. The statistics of the different patterns as a function of the pump power of the laser reveals that the probability for all rogue waves patterns increase close to the laser threshold. We developed a numerical model which prove that the ultrafast rogue waves patterns result from both the polarization mode dispersion in the fiber and the non-instantaneous nature of the saturable absorber. This discovery reveals that there are three different types of rogue waves in fiber lasers: slow, fast, and ultrafast, which relate to three different time-scales and are governed by three different sets of equations: the laser rate equations, the nonlinear Schrodinger equation, and the saturable absorber equations, accordingly. This discovery is highly important for analyzing rogue waves and other extreme events in fiber lasers and can lead to realizing types of rogue waves which were not possible so far such as triangular rogue waves

Designing nanomaterials with desired mechanical properties by constraining the evolution of their grain shapes

Grain shapes are acknowledged to impact nanomaterials' overall properties. Research works on this issue include grain-elongation and grain-strain measurements and their impacts on nanomaterials' mechanical properties. This paper proposes a stochastic model for grain strain undergoing severe plastic deformation. Most models deal with equivalent radii assuming that nanomaterials' grains are spherical. These models neglect true grain shapes. This paper also proposes a theoretical approach of extending existing models by considering grain shape distribution during stochastic design and modelling of nanomaterials' constituent structures and mechanical properties. This is achieved by introducing grain 'form'. Example 'forms' for 2-D and 3-D grains are proposed. From the definitions of form, strain and Hall-Petch-Relationship to Reversed-Hall-Petch-Relationship, data obtained for nanomaterials' grain size and conventional materials' properties are sufficient for analysis. Proposed extended models are solved simultaneously and tested with grain growth data. It is shown that the nature of form evolution depends on form choice and dimensional space. Long-run results reveal that grain boundary migration process causes grains to become spherical, grain rotation coalescence makes them deviate away from becoming spherical and they initially deviate away from becoming spherical before converging into spherical ones due to the TOTAL process. Percentage deviations from spherical grains depend on dimensional space and form: 0% minimum and 100% maximum deviations were observed. It is shown that the plots for grain shape functions lie above the spherical (control) value of 1 in 2-D grains for all considered grain growth mechanisms. Some plots lie above the spherical value, and others approach the spherical value before deviating below it when dealing with 3-D grains. The physical interpretations of these variations are explained from elementary principles about the different grain growth mechanisms. It is observed that materials whose grains deviate further away from the spherical ones have more enhanced properties, while materials with spherical grains have lesser properties. It is observed that there exist critical states beyond which Hall-Petch Relationship changes to Reversed Hall-Petch Relationship. It can be concluded that if grain shapes in nanomaterials are constrained in the way they evolve, then nanomaterials with desired properties can be designed