1. The efficiency of manual editing of high-density surface electromyogram decomposition depends on the recorded muscle and contraction level but less on the operator’s experienceNina Murks, Jakob Škarabot, Matej Kramberger, Matjaž Divjak, Gašper Sedej, Tamara Valenčič, Christopher D. Connelly, Haydn Thomason, Aleš Holobar, 2025, original scientific article Abstract: We investigated the agreement and accuracy of manual editing of the high-density electromyogram (hdEMG) decomposition results by seven human operators with various experience levels. All operators edited the same automatically decomposed experimental hdEMG from the first dorsal interosseous (FDI), tibialis anterior (TA), vastus lateralis (VL), and biceps brachii (BB) muscles, and synthetic hdEMG from soleus (SO) and BB muscles at 10%, 30%, 50% and 70% of maximum voluntary contraction. On average, operators kept 13.7 ± 7.4 motor units (MUs) after editing and demonstrated relatively large disagreement in the calculated MU pulse trains (normalized root mean square difference) but relatively high agreement in the identified MU discharges. Inter-operator agreement positively correlated with the initial MU Pulse-to-Noise Ratio used as a quality measure of automatic MU identification, and negatively correlated with the muscle contraction level. Operators agreed more on the results of the simulated than experimental hdEMG. Among the experimental muscles tested, the greatest agreement was demonstrated for VL and the lowest for BB. We obtained similar results when comparing editing to the results of the most experienced operator and to ground truth in simulated cases: the greatest precision and sensitivity were demonstrated for VL, and the lowest for BB. The level of the operator’s experience had a significant impact on the editing of synthetic hdEMG and the detection of the first MU discharge, but not on the rate of agreement or editing time of experimental hdEMG.
Keywords: hdEMG, manual editing, decomposition results, human operators, motor unit, človeški operaterji
Published in DKUM: 14.10.2025; Views: 0; Downloads: 4
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2. On G-drazin partial order in ringsGregor Dolinar, Bojan Kuzma, Janko Marovt, Dijana Mosić, 2024, original scientific article Abstract: We extend the concept of a G-Drazin inverse from the set Mn of all n × n complex matrices to the set RD of all Drazin invertible elements in a ring R with identity. We also generalize a partial order induced by G-Drazin inverses from Mn to the set of all regular elements in RD , study its properties, compare it to known partial orders, and generalize some known results.
Keywords: drazin inverse, core-nilpotent decomposition, partial order, annihilator, ring
Published in DKUM: 01.07.2025; Views: 0; Downloads: 2
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3. On G-S and C-S inverses in *-ringsJanko Marovt, Dijana Mosić, 2024, original scientific article Abstract: The notions of the G-S inverse and the C-S inverse are extended from the set
of all complex n × n matrices to ∗-rings. We present new characterizations of
these inverses, study their properties, and apply the C-S inverse to introduce
two relations on the set R d© of all core-EP invertible elements in a ∗-ring with
identity. We explore the connection between these two relations and the star
partial order and prove that one of them is a partial order on R d©.
Keywords: *-rings, core-EP decomposition, C-S inverse, C-S partia order, Drazin inverse
Published in DKUM: 01.07.2025; Views: 0; Downloads: 9
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4. The effects of spinal manipulation on motor unit behaviorLucien Robinault, Aleš Holobar, Sylvain Crémoux, Usman Rashid, Imran Khan Niazi, Kelly Holt, Jimmy Lauber, Heidi Haavik, 2021, original scientific article Abstract: Over recent years, a growing body of research has highlighted the neural plastic effects of
spinal manipulation on the central nervous system. Recently, it has been shown that spinal manipulation improved outcomes, such as maximum voluntary force and limb joint position sense, reflecting
improved sensorimotor integration and processing. This study aimed to further evaluate how spinal
manipulation can alter neuromuscular activity. High density electromyography (HD sEMG) signals
from the tibialis anterior were recorded and decomposed in order to study motor unit changes in
14 subjects following spinal manipulation or a passive movement control session in a crossover study
design. Participants were asked to produce ankle dorsiflexion at two force levels, 5% and 10% of
maximum voluntary contraction (MVC), following two different patterns of force production (“ramp”
and “ramp and maintain”). A significant decrease in the conduction velocity (p = 0.01) was observed
during the “ramp and maintain” condition at 5% MVC after spinal manipulation. A decrease in
conduction velocity suggests that spinal manipulation alters motor unit recruitment patterns with an
increased recruitment of lower threshold, lower twitch torque motor units.
Keywords: high-density surface electromyography, chiropractic, electromyography decomposition, motor unit
Published in DKUM: 20.06.2025; Views: 0; Downloads: 6
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6. Improving personalized meal planning with large language models: identifying and decomposing compound ingredientsLeon Kopitar, Leon Bedrač, Larissa Jane Strath, Jiang Bian, Gregor Štiglic, 2025, original scientific article Abstract: Background/Objectives: Identifying and decomposing compound ingredients within meal plans presents meal customization and nutritional analysis challenges. It is essential for accurately identifying and replacing problematic ingredients linked to allergies or intolerances and helping nutritional evaluation. Methods: This study explored the effectiveness of three large language models (LLMs)—GPT-4o, Llama-3 (70B), and Mixtral (8x7B), in decomposing compound ingredients into basic ingredients within meal plans. GPT-4o was used to generate 15 structured meal plans, each containing compound ingredients. Each LLM then identified and decomposed these compound items into basic ingredients. The decomposed ingredients were matched to entries in a subset of the USDA FoodData Central repository using API-based search and mapping techniques. Nutritional values were retrieved and aggregated to evaluate accuracy of decomposition. Performance was assessed through manual review by nutritionists and quantified using accuracy and F1-score. Statistical significance was tested using paired t-tests or Wilcoxon signed-rank tests based on normality. Results: Results showed that large models—both Llama-3 (70B) and GPT-4o—outperformed Mixtral (8x7B), achieving average F1-scores of 0.894 (95% CI: 0.84–0.95) and 0.842 (95% CI: 0.79–0.89), respectively, compared to an F1-score of 0.690 (95% CI: 0.62–0.76) from Mixtral (8x7B). Conclusions: The open-source Llama-3 (70B) model achieved the best performance, outperforming the commercial GPT-4o model, showing its superior ability to consistently break down compound ingredients into precise quantities within meal plans and illustrating its potential to enhance meal customization and nutritional analysis. These findings underscore the potential role of advanced LLMs in precision nutrition and their application in promoting healthier dietary practices tailored to individual preferences and needs.
Keywords: artificial intelligence, food analysis, LLM, Ilama, GPT, mixtral, ingredient identification, ingredient decomposition, personalized nutrition, meal customization, nutritional analysis, dietary planning
Published in DKUM: 08.05.2025; Views: 0; Downloads: 3
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7. Task-oriented evaluation of the feasible kinematic directional capabilities for robot machiningSaša Stradovnik, Aleš Hace, 2022, original scientific article Abstract: Performing the machining of complex surfaces can be a challenging task for a robot, especially in terms of collaborative robotics, where the available motion capabilities are greatly reduced
in comparison with conventional industrial robot arms. It is necessary to evaluate these capabilities
prior to task execution, for which we need efficient algorithms, especially in the case of flexible
robot applications. To provide accurate and physically consistent information about the maximum
kinematic capabilities while considering the requirements of the task, an approach called the Decomposed Twist Feasibility (DTF) method is proposed in this study. The evaluation of the maximum
feasible end-effector velocity is based on the idea of decomposition into the linear and angular motion
capabilities, considering a typical robot machining task with synchronous linear and angular motion.
The proposed DTF method is presented by the well-known manipulability polytope concept. Unlike
the existing methods that estimate the kinematic performance capabilities in arbitrarily weighted
twist space, or separately in the translation and the rotation subspace, our approach offers an accurate
and simple solution for the determination of the total kinematic performance capabilities, which is
often highly required, especially in the case of robot machining tasks. The numerical results obtained
in this study show the effectiveness of the proposed approach. Moreover, the proposed DTF method
could represent suitable kinematic performance criteria for the optimal placement of predefined tasks
within the robot workspace
Keywords: robot surface machining, task feasibility, task-dependent kinematic capability, kinematic performance evaluation, manipulability index, manipulability polytope, motion decomposition, Decomposed Twist Feasibility method, DTF method
Published in DKUM: 01.04.2025; Views: 0; Downloads: 5
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8. Identification of motor unit firings in H-reflex of soleus muscle recorded by high-density surface electromyographyMiloš Kalc, Jakob Škarabot, Matjaž Divjak, Filip Urh, Matej Kramberger, Matjaž Vogrin, Aleš Holobar, 2023, original scientific article Keywords: motor units identification, high-density surface EMG, decomposition, H-reflex
Published in DKUM: 13.06.2024; Views: 133; Downloads: 15
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10. Optimization of conditions for enzymatic decomposition of fibrous cotton textile waste : diplomsko delo univerzitetnega študijskega programa I. stopnjeStela Tashkova, 2023, undergraduate thesis Abstract: The main goal of this thesis was to optimize the conditions under which a 100 % cellulose material enzymatically decomposes. Waste textile and waste cellulose represent a large source of carbon that can be used in the production of value–added chemicals. The main goal of this diploma thesis was to test different conditions for the enzymatic decomposition of cellulose waste such as temperature range, enzymes concentration and different buffer composition. We started with the optimization of the temperature and tested how the reaction proceeds at three different temperatures (50, 55 and 60 °C). Here, the main goal was to check how the enzymatic mixture we used acts at these three different environments, thus how much will the material decompose. The results showed that the optimal temperature for the decomposition of cellulose is 50 °C. The second part of the diploma thesis evaluates if a higher concentration of enzymes would get better results regarding cellulose waste decomposition. The results here showed that an increased enzyme concentration does not improve the efficiency of the reaction under the tested conditions. Additionally, two different buffers 0.1 M NH4Cl and 0.1 M (NH4)2SO4 were tested as environments for the enzymatic degradation of cellulose waste. We got a higher glucose concentration in the reaction with (NH4)2SO4, as well as less variability of the pH, which led to a lower NaOH consumtion.
Keywords: enzymatic cellulose decomposition, optimization, temperature effect, NH4Cl, (NH4)2SO4, Cellic® CTec2
Published in DKUM: 13.09.2023; Views: 373; Downloads: 22
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