Małgorzata Jakubowska

A Controlled Proof-of-Concept Study for Quantitative Estimation of Syrup Addition in Honey Using RGB Histogram Descriptors and Explainable Machine Learning

Małgorzata Dziubaniuk, Patrycja Kwiek, Małgorzata Jakubowska

This controlled proof-of-concept study evaluated whether interpretable RGB histogram descriptors extracted from smartphone images can be used to estimate nominal syrup addition within a single experimentally prepared honey-adulterant series. Eleven concentration-specific physical mixtures containing 0–50% syrup in 5% increments were prepared, and …

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Color Representation and Prediction Uncertainty in Unsupervised Retinal Vessel Segmentation

Patrycja Kwiek, Małgorzata Jakubowska

This study investigates the influence of color representation, preprocessing, and thresholding strategies on unsupervised retinal vessel segmentation using computationally efficient classical image processing techniques. Nineteen image channels derived from RGB, HSV, HSL, YUV, YCrCb, CIELAB, and grayscale representations were evaluated in combination …

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Explainability of linear and nonlinear regression models in voltammetric analytical signals using SHAP

Patrycja Kwiek, Valentin Mirceski, Szymon Wójcik, Katarzyna Jedlińska et autres

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Graphene-Patterned Polymeric Substrates for Enhanced Tissue Proliferation

Weronika Sosnowicz, Jakub Krzemiński, Jan Dominiczak, Dominik Baraniecki et autres

INTRODUCTION: In tissue engineering, there is a growing need for patient-specific strategies that enable precise control of cellular behaviour - such as adhesion, proliferation, and migration - to enhance tissue integration and reduce transplant rejection. Engineering the physicochemical properties and topography of …

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Automatic Baseline Correction of 1D Signals Using a Parameter-Free Deep Convolutional Autoencoder Algorithm

Łukasz Górski, Małgorzata Jakubowska

Baseline correction techniques are highly applicable in analytical chemistry. Consequently, there is a constant demand for universal and automated baseline correction methods. Our new procedure, based on the Convolutional Autoencoder (ConvAuto) model and combined with an automated implementation algorithm (ApplyModel procedure), meets …

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Color Space Channel Evaluation for Clahe-Enhanced Retinal Vessel Segmentation With Attention U-Net

Patrycja Kwiek, Małgorzata Jakubowska

Accurate segmentation of retinal blood vessels plays a crucial role in the early diagnosis and monitoring of systemic and ophthalmological diseases, such as diabetic retinopathy and hypertension. While many existing approaches rely on grayscale or RGB image representations, this work explores the …

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Development of environmentally friendly flexible electronics based on ethyl cellulose – silver microflakes composite

Bartosz Zdanikowski, Jerzy Szałapak, Aleksandra Kądziela, Tomislav Cigula et autres

• Eco-friendly composite with ethyl cellulose and silver microflakes was developed. • Composite enables low temperature curing and is fit for silver recycling. • Screen-printed layers showed low sheet resistance and strong adhesion to paper. • Bending increased resistance by 20%, but …

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Automatic Baseline Correction of 1D Signals Using a Parameter-Free Deep Convolutional Autoencoder Algorithm

Łukasz Górski, Małgorzata Jakubowska

Baseline correction techniques are highly applicable in analytical chemistry. Consequently, there is a constant demand for universal and automated baseline correction methods. Our new procedure based on the Convolutional Autoencoder model (ConvAuto model) combined with an automated algorithm to Apply the Model …

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Spectrometry of Captured Highly Charged Ions Produced Following Antiproton Annihilations

Fredrik Parnefjord Gustafsson, Marco Volponi, J. Zieliński, A. Asare et autres

We report a proof-of-principle study demonstrating the first capture and time-of-flight spectrometry of highly charged ions (HCIs) produced following antiproton annihilations in a Penning-Malmberg trap. A multi-step nested-trap technique was developed using the \aegis\ experiment to identify annihilation-linked captured ions. The trapping …

Color-Guided Mixture-of-Experts Conditional GAN for Realistic Biomedical Image Synthesis in Data-Scarce Diagnostics

Patrycja Kwiek, Filip Ciepiela, Małgorzata Jakubowska

Background: Limited availability of high-quality labeled biomedical image datasets presents a significant challenge for training deep learning models in medical diagnostics. This study proposes a novel image generation framework combining conditional generative adversarial networks (cGANs) with a Mixture-of-Experts (MoE) architecture and color …

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Sustainable electrodes for biosignal sensing based on cellulose and marine sponges

Leszek Kołodziej, Olga Iwasińska-Kowalska, Grzegorz Wróblewski, Małgorzata Jakubowska et autres

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Eco-friendly and cytocompatible graphene composite based on water-soluble biopolymers for modern printed electronics and beyond

Aleksandra Kądziela, Sandra Lepak-Kuc, Zofia Szczesiul, Arkadiusz Jeznach et autres

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