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Micro-CT, Mechanical, and Histological Examination of the Effect of Local Adjuvants on Porcine Cortical Bone Following Intralesional Curettage of Bone Tumors
(Springer Nature, 2024-05-14) Apostolopoulos, Vasileios; Boháč, Petr; Marcián, Petr; Staniczková Zambo, Iva; Pazourek, Lukáš; Mahdal, Michal; Neradil, Jakub; Návrat, Tomáš; Tomáš, Tomáš
Background and Objectives Curettage is the removal of a tumor from the bone while preserving the surrounding healthy cortical bone, and is associated with higher rates of local recurrence. To lower these rates, curettage should be combined with local adjuvants, although their use is associated with damage to nearby healthy bone. Objective The purpose of this analysis is to determine the effect of local adjuvants on cortical porcine bone by using micro-computed tomography (micro-CT) along with histological and mechanical examination. Methods Local adjuvants were applied to porcine specimens under defined conditions. To assess changes in bone mineral density (BMD), a micro-CT scan was used. The pixel gray values of the volume of interest (VOI) were evaluated per specimen and converted to BMD values. The Vickers hardness test was employed to assess bone hardness (HV). The depth of necrosis was measured histologically using hematoxylin and eosin-stained tissue sections. Results A noticeable change in BMD was observed on the argon beam coagulation (ABC) sample. Comparable hardness values were measured on samples following electrocautery and ABC, and lowering of bone hardness was obtained in the case of liquid nitrogen. Extensive induced depth of necrosis was registered in the specimen treated with liquid nitrogen. Conclusion This study determined the effect of local adjuvants on cortical bone by using micro-CT along with histological and mechanical examination. Phenolization and liquid nitrogen application caused a decrease in bone hardness. The bone density was affected in the range of single-digit percentage values. Liquid nitrogen induced extensive depth of necrosis with a wide variance of values.
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Ultra-Cycling- Past, Present, Future: A Narrative Review
(SpringerOpen, 2024-04-29) Tiemeier, Lucas; Nikolaidis, Pantelis T.; Chlíbková, Daniela; Wilhelm, Matthias; Thuany, Mabliny; Weiss, Katja; Knechtle, Beat
Background: Ultra-endurance events are gaining popularity in multiple exercise disciplines, including cycling. With increasing numbers of ultra-cycling events, aspects influencing participation and performance are of interest to the cycling community. Main body: The aim of this narrative review was, therefore, to assess the types of races offered, the characteristics of the cyclists, the fluid and energy balance during the race, the body mass changes after the race, and the parameters that may enhance performance based on existing literature. A literature search was conducted in PubMed, Scopus, and Google Scholar using the search terms 'ultracycling', 'ultra cycling', 'ultra-cycling', 'ultra-endurance biking', 'ultra-bikers' and 'prolonged cycling'. The search yielded 948 results, of which 111 were relevant for this review. The studies were classified according to their research focus and the results were summarized. The results demonstrated changes in physiological parameters, immunological and oxidative processes, as well as in fluid and energy balance. While the individual race with the most published studies was the Race Across America, most races were conducted in Europe, and a trend for an increase in European participants in international races was observed. Performance seems to be affected by characteristics such as age and sex but not by anthropometric parameters such as skin fold thickness. The optimum age for the top performance was around 40 years. Most participants in ultra-cycling events were male, but the number of female athletes has been increasing over the past years. Female athletes are understudied due to their later entry and less prominent participation in ultra-cycling races. A post-race energy deficit after ultra-cycling events was observed. Conclusion: Future studies need to investigate the causes for the observed optimum race age around 40 years of age as well as the optimum nutritional supply to close the observed energy gap under consideration of the individual race lengths and conditions. Another research gap to be filled by future studies is the development of strategies to tackle inflammatory processes during the race that may persist in the post-race period.
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Monte Carlo tree search control scheme for multibody dynamics applications
(Springer Nature, 2024-04-03) Tang, Yixuan; Orzechowski, Grzegorz; Prokop, Aleš; Mikkola, Aki
There is considerable interest in applying reinforcement learning (RL) to improve machine control across multiple industries, and the automotive industry is one of the prime examples. Monte Carlo Tree Search (MCTS) has emerged and proven powerful in decision-making games, even without understanding the rules. In this study, multibody system dynamics (MSD) control is first modeled as a Markov Decision Process and solved with Monte Carlo Tree Search. Based on randomized search space exploration, the MCTS framework builds a selective search tree by repeatedly applying a Monte Carlo rollout at each child node. However, without a library of available choices, deciding among the many possibilities for agent parameters can be intimidating. In addition, the MCTS poses a significant challenge for searching due to the large branching factor. This challenge is typically overcome by appropriate parameter design, search guiding, action reduction, parallelization, and early termination. To address these shortcomings, the overarching goal of this study is to provide needed insight into inverted pendulum controls via vanilla and modified MCTS agents, respectively. A series of reward functions are well-designed according to the control goal, which maps a specific distribution shape of reward bonus and guides the MCTS-based control to maintain the upright position. Numerical examples show that the reward-modified MCTS algorithms significantly improve the control performance and robustness of the default choice of a constant reward that constitutes the vanilla MCTS. The exponentially decaying reward functions perform better than the constant value or polynomial reward functions. Moreover, the exploitation vs. exploration trade-off and discount parameters are carefully tested. The study’s results can guide the research of RL-based MSD users.
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Measurement and Analysis of 4G/5G Mobile Signal Coverage in a Heavy Industry Environment
(MDPI, 2024-04-15) Polák, Ladislav; Kufa, Jan; Šotner, Roman; Frýza, Tomáš
In the evolving landscape of Industry 4.0, the integration of advanced wireless technologies into manufacturing processes holds the promise of unprecedented connectivity and efficiency. In particular, the data transmission in a heavy industry environment needs stable connectivity with mobile operators. This paper deals with the performance study of 4G and 5G mobile signal coverage within a complex factory environment. For this purpose, a cost-effective and portable measurement setup was realized and used to provide long-term measurement campaigns monitoring and recording several key parameter indicators (KPIs) in 4G/5G downlink and upload. To support the reproducibility of the provided study and other research activities, the measured dataset is publicly available for download. Among others findings, the obtained results show how the performance of 4G/5G is influenced by a heavy industry environment and of the time of day on the network load.
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Metody hlubokého učení pro segmentaci elektrokardiografických signálů
(Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, ) Hejč, Jakub; Kolářová, Jana; Černý, Martin; Halámek, Josef
Práce se zabývá metodami hlubokého učení pro segmentaci elektrokardiografických záznamů z povrchového a intrakardiálního snímání se zaměřením na síňovou aktivitu. Teoretická část seznamuje se současnými přístupy segmentace a s problematikou spojenou s využíváním standardních EKG databází pro vývoj hlubokých modelů. V práci byl navržen řetězec metod pro zpracování multimodálních dat z elektrofyziologického vyšetření. Tyto metody byly následně využity pro sestavení trénovacích datových sad. V práci byl navržen hluboký model pro segmentaci intrakardiálních záznamů založený na modifikované architektuře s reziduálním spojením. Byla provedena série experimentů sledující vliv nastavení modelu a předzpracování datové sady na kvalitu segmentace. Jako zásadní činitel se ukázala přítomnost a způsob anotace záznamů s fibrilací síní. Mezi další významné parametry patřilo nastavení penalizační funkce a způsob augmentace trénovacích dat. V práci byla dále navržena nová metoda segmentace P vln využívající neúplné reference. Přístup byl inspirován metodou hlubokého kontrastního učení, která byla modifikována pro odlišení lokálních úseků signálů na různých úrovních abstrakce extrahovaných příznakových map. Výsledky byly analyzovány pomocí standardních metrik kvality a post-hoc vizuální analýzou. V dílčích případech bylo provedeno statistické srovnání experimentů pro různá nastavení. Výsledky práce ukázaly, že je možné využít intrakardiální signály pro zabudování vektorové reprezentace lokální síňové aktivace do hlubokých modelů.