20883 research outputs found
Sort by
Vpliv nekaterih gibalnih in funkcionalnih sposobnosti na tekmovalno uspešnost v alpskem smučanju
Get PDF
Estimation of task-related dynamic brain connectivity via data inflation and classification model explainability
Get PDFStudy of brain function often involves analyzing task-related switching between intrinsic brain networks, which connect various brain regions. Functional brain connectivity analysis methods aim to estimate these networks but are limited by the statistical constraints of windowing functions, which reduce temporal resolution and hinder explainability of highly dynamic processes. In this work, we propose a novel approach to functional connectivity analysis through the explainability of EEG classification. Unlike conventional methods that condense raw data into extracted features, our approach inflates raw EEG data by decomposition into meaningful components that explain processes in the application domain. To uncover the brain connectivity that affects classification decisions, we introduce a new method of dynamic influence data inflation (DIDI), which extracts signals representing interactions between electrode regions. These inflated data are then classified using an end-to-end neural network classifier architecture designed for raw EEG signals. Saliency map estimation from trained classifiers reveals the connectivity dynamics affecting classification decisions, which can be visualized as dynamic connectivity support maps for improved interpretability. The methodology is demonstrated on two publicly available datasets: one for imagined motor movement classification and the other for emotion classification. The results highlight the dual benefits of our approach: in addition to providing interpretable insights into connectivity dynamics it increases classification accuracy
The influence of bacterial inoculants and a biofertilizer on maize cultivation and the associated shift in bacteriobiota during the growing season
Get PDFMaize (Zea mays L.) relies heavily on nitrogen and phosphorus inputs, typically supplied through organic and inorganic fertilizers. However, excessive agrochemical use threatens soil fertility and environmental health. Sustainable alternatives, such as poultry manure (PM) and plant growth-promoting rhizobacteria (PGPR), offer promising solutions. This study examines the effects of a phytobiotic bacterial formulation (PHY), composed of Bacillus subtilis and Microbacterium sp., applied alone and in combination with PM, on maize’s rhizosphere bacteriobiome across key growth stages. Field trials included four treatments: a control, PHY-coated seeds, PM, and combined PHY_PM. The results show that early in development, the PM-treated rhizospheres increased the abundance of beneficial genera such as Sphingomonas, Microvirga, and Streptomyces, though levels declined in later stages. The PHY_PM-treated roots in the seedling phase showed a reduced abundance of taxa like Chryseobacterium, Pedobacter, Phyllobacterium, Sphingobacterium, and Stenotrophomonas, but this effect did not persist. In the PM-treated roots, Flavisolibacter was significantly enriched at harvesting. Overall, beneficial bacteria improved microbial evenness, and the PHY_PM treatment promoted bacterial diversity and maize growth. A genome analysis of the PHY strains revealed plant-beneficial traits, including nutrient mobilization, stress resilience, and biocontrol potential. This study highlights the complementarity of PM and PGPR, showing how their integration reshapes bacteriobiome and correlates with plant parameters in sustainable agriculture
Nelinearna avtoregresija EEG signalov za izboljšano analizo funcijske možganske povezljivosti
Get PDF
