Objective(s): Non-invasive treatment options for retinoblastoma (RB), the most common malignant eye tumor among children, are lacking. Epithelial growth factor receptor (EGFR) accelerates cell proliferation, survival, and invasion of many tumors including RB. However, RB treatment by targeting EGFR has not yet been researched. In the current study, we investigated the effect of EGFR down-regula...

We present a topological approach to the input-output relations of photonic driven-dissipative lattices acting as directional amplifiers. Our theory relies on mapping from optical non-Hermitian coupling matrix an effective insulator Hamiltonian. This is based singular value decomposition matrices, whose inverse determines linear response system. In topologically non-trivial regimes, lattice dom...

We show that a stably ergodic diffeomorphism can be C approximated by a diffeomorphism having stably non-zero Lyapunov exponents. Two central notions in Dynamical Systems are ergodicity and hyperbolicity. In many works showing that certain systems are ergodic, some kind of hyperbolicity (e.g. uniform, non-uniform or partial) is a main ingredient in the proof. In this note the converse direction...

where x is an n-dimensional vector of variables, A is an m × n matrix, b is the RHS vector and the vectors ci (i = 1, ...,m) represent the coefficients of the objective functions (criteria). Let’s denote yi = fi(x), i = 1, ...,m, and let y = (y1, ..., ym) be a vector in the criteria space. The set Y ⊂ Rm composed by all possible criterion vectors y = f(x) when x ∈ X, is known as Feasible Criter...

The feature map represented by the set of weight vectors of the basic SOM (Self-Organizing Map) provides a good approximation to the input space from which the sample vectors come. But the timedecreasing learning rate and neighborhood function of the basic SOM algorithm reduce its capability to adapt weights for a varied environment. In dealing with non-stationary input distributions and changi...

A model for non-Gaussian random vectors is presented that relies on a modification of the standard translation transformation which has previously been used to model stationary non-Gaussian processes and non-Gaussian random vectors with identically distributed components. The translation model has the ability to exactly match target marginal distributions and a broad variety of correlation matr...