Papers by Dimiter Prodanov
... ITEM METADATA RECORD. Title: Evaluation of planar micro-fabricated multi-electrode arrays for... more ... ITEM METADATA RECORD. Title: Evaluation of planar micro-fabricated multi-electrode arrays for neuronal recording in vivo. Authors: Prodanov, Dimiter Musa, Silke Welkenhuysen, Marleen Eberle, Wolfgang Bartic, Carmen Borghs, Gustaaf Nuttin, B. Issue Date: Nov-2009. ...
Single-channel neural signal recordings were obtained from deep brain region in normal rats and r... more Single-channel neural signal recordings were obtained from deep brain region in normal rats and rats conditioned as an animal model for human obsessive-compulsive disorder (OCD), both in anesthetized condition. Artifact noise of consistent 70Hz repetition frequency and its ...
arXiv: Classical Analysis and ODEs, 2019
From physical perspective, derivatives can be viewed as mathematical idealizations of the linear ... more From physical perspective, derivatives can be viewed as mathematical idealizations of the linear growth. The linear growth condition has special properties, which make it preferred. The manuscript investigates the general properties of the local generalizations of derivatives assuming the usual topology of the real line. The concept of derivative is generalized in terms of the class of the modulus of continuity of the primitive function. This definition is suitable for applications involving continuous but possibly non-absolutely continuous functions of a real variable. The main application of the approach is the generalization of the Lebesgue monotone differentiation theorem. On the second place, the conditions of continuity of generalized derivative are also demonstrated.
Chaos, Solitons & Fractals, 2021
The present work demonstrates the connections between the Burgers, diffusion, and Schrödinger's e... more The present work demonstrates the connections between the Burgers, diffusion, and Schrödinger's equations. The starting point is a formulation of the stochastic mechanics, which is modelled along the lines of the scale relativity theory. The resulting statistical description obeys the Fokker-Planck equation. This paper further demonstrates the connection between the two approaches, embodied by the study of the Burgers equation, which from this perspective appears as a stochastic geodesic equation. The main result of the article is the transparent derivation of the Born rule from the starting point of a complex stochastic process, based on a complex Fokker-Planck formalism.
Multiples lines of evidence indicate that spatial 3D organisation nuclear DNA is critical in adap... more Multiples lines of evidence indicate that spatial 3D organisation nuclear DNA is critical in adapting to different environmental conditions and the Impact of Nuclear Domains On Gene Expression and Plant Traits (INDEPTH) network aims to decipher how nuclear architecture, chromatin organisation and gene expression are connected and modified in response to internal and external cues.
Nucleus, 2019
The eukaryotic cell nucleus is a central organelle whose architecture determines genome function ... more The eukaryotic cell nucleus is a central organelle whose architecture determines genome function at multiple levels. Deciphering nuclear organizing principles influencing cellular responses and identity is a timely challenge. Despite many similarities between plant and animal nuclei, plant nuclei present intriguing specificities. Complementary to molecular and biochemical approaches, 3D microscopy is indispensable for resolving nuclear architecture. However, novel solutions are required for capturing cell-specific, sub-nuclear and dynamic processes. We provide a pointer for utilising high-to-super-resolution microscopy and image processing to probe plant nuclear architecture in 3D at the best possible spatial and temporal resolution and at quantitative and cellspecific levels. High-end imaging and image-processing solutions allow the community now to transcend conventional practices and benefit from continuously improving approaches. These promise to deliver a comprehensive, 3D view of plant nuclear architecture and to capture spatial dynamics of the nuclear compartment in relation to cellular states and responses.
Parallelization of image processing algorithms can be achieved either on the Central Processing U... more Parallelization of image processing algorithms can be achieved either on the Central Processing Unit (CPU) or on the Graphics Processing Unit (GPU) side. High level support of parallelization schemes is still minimally developed in Java, which is a definite disadvantage compared to C++ and C#. The support of GPU parallel image processing in Java is still minimal and depends on custom libraries. The availability of image processing frameworks in Java, such as ImageJ, together with the potential of GPUs to offer high performance at low cost makes it attractive to bridge this gap. On the other hand, the advantages of GPU parallel architecture are penalized by the memory transfer overheads, which make GPU implementation of certain classes of algorithms not useful. In this work we demonstrate a combined Java and CUDA based implementation for the basic morphological operations and spatial convolution. It is demonstrated that the overhead of Java is negligible, which presents a viable option for integration of GPU code into Java programs. The CUDA-enabled GPUs have four types of memory, notably global memory, constant memory, texture memory and shared memory. The results indicate that the most advantageous GPU implementation is by using texture memory. Our results show an advantage of GPU parallelization over sequential implementation on the CPU for both convolutions and mathematical morphology operations. Using 3x3 kernel, on a NVIDIA GeForce GTX 470 platform the speedup of the CUDA processing was ranging from 177 to 208 times for convolution and dilation respectively .
Brain Sciences
Image segmentation still represents an active area of research since no universal solution can be... more Image segmentation still represents an active area of research since no universal solution can be identified. Traditional image segmentation algorithms are problem-specific and limited in scope. On the other hand, machine learning offers an alternative paradigm where predefined features are combined into different classifiers, providing pixel-level classification and segmentation. However, machine learning only can not address the question as to which features are appropriate for a certain classification problem. The article presents an automated image segmentation and classification platform, called Active Segmentation, which is based on ImageJ. The platform integrates expert domain knowledge, providing partial ground truth, with geometrical feature extraction based on multi-scale signal processing combined with machine learning. The approach in image segmentation is exemplified on the ISBI 2012 image segmentation challenge data set. As a second application we demonstrate whole ima...
Applied Mathematical Modelling, 2021
Abstract In their article, N. A. Kudryashov, M. A. Chmykhov, M. Vigdorowitsch, “Analytical featur... more Abstract In their article, N. A. Kudryashov, M. A. Chmykhov, M. Vigdorowitsch, “Analytical features of the SIR model and their applications to COVID-19”, Applied Mathematical Modelling 90 (2021) 466–473, aimed to establish the relationships among S, I and R populations, as well as to suggest a form for the exact solution of the SIR model. One of the equations given there is not correct, which leads to an error in the solution. The objective of the present letter is to present the correct parametric solution and to discuss its numerical approximation by direct quadrature.
Advances in Applied Clifford Algebras, 2016
Clifford algebras have broad applications in science and engineering. The use of Clifford algebra... more Clifford algebras have broad applications in science and engineering. The use of Clifford algebras can be further promoted in these fields by availability of computational tools that automate tedious routine calculations. We offer an extensive demonstration of the applications of Clifford algebras in electromagnetism using the geometric algebra G 3 ≡ Cℓ3,0 as a computational model in the Maxima computer algebra system. We compare the geometric algebra-based approach with conventional symbolic tensor calculations supported by Maxima, based on the itensor package. The Clifford algebra functionality of Maxima is distributed as two new packages called clifford-for basic simplification of Clifford products, outer products, scalar products and inverses; and cliffordan-for applications of geometric calculus.
arXiv: Classical Analysis and ODEs, 2016
H\"older functions represent mathematical models of nonlinear physical phenomena. This work ... more H\"older functions represent mathematical models of nonlinear physical phenomena. This work investigates the general conditions of existence of fractional velocity as a localized generalization of ordinary derivative with regard to the exponent order. Fractional velocity is defined as the limit of the difference quotient of the function's increment and the difference of its argument raised to a fractional power. A relationship to the point-wise H\"older exponent of a function, its point-wise oscillation and the existence of fractional velocity is established. It is demonstrated that wherever the fractional velocity of non-integral order is continuous then it vanishes. The work further demonstrates the use of fractional velocity as a tool for characterization of the discontinuity set of the derivatives of functions thus providing a natural characterization of strongly non-linear local behavior. Finally the equivalence with the Kolwankar-Gangal local fractional derivativ...
The chapter introduces multiscale methods for image analysis and their applications to segmentati... more The chapter introduces multiscale methods for image analysis and their applications to segmentation of microscopic images. Specifically, it presents mathematical morphology and linear scale-space theories as overarching signal processing frameworks without excessive mathematical formalization. The chapter introduces several differential invariants, which are computed from parametrized Gaussian kernels and their derivatives. The main application of this approach is to build a multidimensional multiscale feature space, which can be subsequently used to learn characteristic fingerprints of the objects of interests. More specialized applications, such as anisotropic diffusion and detection of blob-like and fiber-like structures, are introduced for two-dimensional images, and extensions to three-dimensional images are discussed. Presented approaches are generic and thus have broad applicability to time-varying signals and to twoand three-dimensional signals, such as microscopic images. T...
Journal of Pharmacological and Toxicological Methods, 2017
Dries Braeken , Action potential-based MEA platform for in vitro screening of drug-induced cardio... more Dries Braeken , Action potential-based MEA platform for in vitro screening of drug-induced cardiotoxicity using human iPSCs and rat neonatal myocytes,
arXiv: Tissues and Organs, 2015
Implantation of neuroprosthetic electrodes induces a stereotypical state of neuroinflammation, wh... more Implantation of neuroprosthetic electrodes induces a stereotypical state of neuroinflammation, which is thought to be detrimental for the neurons surrounding the electrode. Mechanisms of this type of neuroinflammation are still not understood well. Recent experimental and theoretical results point out possible role of the diffusion species in this process. The paper considers a model of anomalous diffusion occurring in the glial scar around a chronic implant in two simple geometries -- a separable rectilinear electrode and a cylindrical electrode, which are solvable exactly. We describe a hypothetical extended source of diffusing species and study its concentration profile in steady-state conditions. Diffusion transport is assumed to obey a fractional-order Fick law, which is derived from physically realistic assumptions using a fractional calculus approach. The derived fractional-order distribution morphs into regular order diffusion in the case of integer fractional exponents. The...
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Papers by Dimiter Prodanov