Tomas Bata University in Zlín
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Effect of UV exposure time on the properties of films prepared from biotechnologically derived chicken gelatin
Get PDFBiomaterials (films, foils, fibers, coatings) based on proteins are becoming increasingly important due to the growing applications for which pork and beef gelatins are used. Alternative types of gelatins (poultry or fish), which have not yet been sufficiently tested, represent a high potential. This study looks at the effect of different UV exposure times on chicken gelatin films with added glycerol. The gelatin was prepared using a unique enzymatic hydrolysis process. The quality of the UV-exposed films was compared with gelatin films not exposed to UV light. Radiation-induced crosslinking improved the mechanical and physical properties of the films. The UV crosslinked films are stabilized at a degree of swelling from 700 to 900%; moreover, they extend their dissolution to more than 7 days while maintaining their original shape. In contrast, non-crosslinked films swell and dissolve in water faster. Further, the effect of UV radiation on the water vapor permeability and color of the films was monitored. Water vapor permeability decreased by 2.5 times with increasing crosslinking time for 30% and 40% glycerol content, and the yellowness of the irradiated samples increased with exposure time in the interval from 24 to 28. Using Fourier transform infrared spectroscopy, the differences in the amount of bonding based on irradiation time were analyzed. As a result of crosslinking, the intensity of existing bonds increased. Thermal properties were verified through differential scanning calorimetry and thermogravimetric analysis. The results proved that chicken gelatin is suitable for preparing films in foods and medicine. Applying UV radiation to crosslink gelatin films is an alternative to traditionally used chemical crosslinkers.Faculty of Technology of Tomas Bata University in Zlin [IGA/FT/2024/008
Influence of injection molding parameters and distance from gate on the mechanical properties of injection-molded polypropylene
Get PDFThis publication deals with the study of the mechanical properties of injection-molded polypropylene parts depending on the process parameters and the distance from the gate location in which the mechanical properties were investigated. Due to the fact that the mechanical properties of injection-molded parts are not the same at all locations, this research was designed to investigate the inhomogeneity of the properties of injection-molded parts along the length of the product. The inhomogeneity is affected by various influences, including distance from the sprue mouth, melt and mold temperature, injection pressure, crystal structure, and others. It was demonstrated that mechanical properties are not uniform over the entire injected product. Contrary to popular belief, mechanical properties can vary along the flow length due to uneven cooling and process parameters. Injection pressure and mold temperature significantly affect the mechanical properties of the injection-molded parts. The limiting injection pressure is 40 MPa and the mold temperature is 40 °C. The difference in individual spots in an injected article was up to 37%. Changes in mechanical properties are closely related to changes in morphology (crystallinity measured by DSC) caused by different injection molding process parameters. As is evident from the aforementioned results, the possible benefits of this work for injection molding of polymer products are apparent. Suitably chosen gate location, surface of the cavity, and process parameters can ensure targeted improvement of mechanical properties in stressed parts of a product.Internal Grant Agency of Tomas Bata University in Zlin, (IGA/FT/2025/002)Internal Grant Agency of Tomas Bata University [IGA/FT/2025/002]; Internal Grant Agency of Tomas Bata University in Zli
Machine learning approach for photocatalysis: An experimentally validated case study of photocatalytic dye degradation
No full textIn this study, machine learning (ML) models coupled with genetic algorithm (GA) and particle swarm optimization (PSO) were applied to predict the relative influence of experimental parameters of photocatalytic dye removal. Specifically, the impact of bandgap, dye concentration, photocatalyst dosage, solution volume, specific surface area, and time duration on photocatalytic degradation rate constant of cationic dyes was discerned using selected ML models, i.e., ensembled learning tree (ELT), gaussian process regression (GPR), support vector machine (SVM), and decision tree (DT). Thus, the data points were sourced from literature studies recently published in 2024 and 2023 on materials related to working on fundamental principles of photocatalysis. The ELT-PSO hybrid model outperformed all models with R2 = 0.992 and RMSE = 2.6408e−04, followed by DT, GPR, and SVM. The partial dependence plots and Shapley's analysis demonstrate that the type of dye, bandgap, dye initial concentration, and time duration are essential parameters for photocatalytic degradation, while sensitivity analysis further displayed solution volume and time duration to be the most influential parameters for rate constant determination. The optimized ML model's prediction was also experimentally validated using as-synthesized different compositions of Cu2O/WO3 heterostructures and ZnO nanoparticles. The results suggest that an ML-optimized study can be used in designing photocatalysts with optimum properties desired for the removal of cationic dyes at high rates from wastewater, thus saving energy and cost for a sustainable environment.European Just Transition Fund; Intelligence & Talent for the Zlin Region; Coimbatore Institute of Technology, CIT; SVM; Ministerstvo Školství, Mládeže a Tělovýchovy, MSMT; DKRVO, (RP/CPS/2024-28/007, RP/CPS/2024-28/002); Ministerstvo Životního Prostředí, MZP, (CZ.02.01.01/00/23_021/0009004, CZ.10.03.01/00/22_003/0000045); Ministerstvo Životního Prostředí, MZPEuropean Just Transition Fund of the Ministry of the Environment of the Czech Republic [CZ.02.01.01/00/23_021/0009004]; Ministry of Education, Youth, and Sports of the Czech Republic-DKRVO [RP/CPS/2024-28/002, RP/CPS/2024-28/007]; The "Creativity, Intelligence & Talent for the Zlin Region" (CIT-ZK) program; [CZ.10.03.01/00/22_003/0000045
Economic policy uncertainty and renewable energy transition: Assessing the impact of resource richness, environmental technology, and environmental governance
No full textThe urgency of transitioning to renewable energy is a core priority under the United Nations Sustainable Development Goals (SDGs). However, economic policy uncertainty (EPU) remains a significant challenge in achieving a stable and sustained renewable energy transition (RET), particularly in resource-rich regions such as the Arctic Council countries (Sweden, the United States, Finland, Norway, Canada, Russia, and Denmark). Despite the wealth of literature on RET, research on the Arctic region remains scarce, particularly regarding the interplay between EPU, resource abundance, environmental technology, and governance. This research fills the gap by examining the impact of these factors on RET in the Arctic from 1990 to 2020, employing the Method of moment quantile regression (MMQR) approach to capture heterogeneous effects across different quantiles of RET distribution. The empirical findings reveal that a 1 % rise in economic policy uncertainty leads to a decline in RET between 0.287 % and 0.557 % across different quartiles, indicating a robust negative impact. Conversely, a 1 % increase in natural resource endowment (0.108 %–0.402 %), environmental technology (0.408 %–0.810 %), and environmental governance (0.216 %–0.633 %) enhances RET, with varying degrees of intensity across RET distributions. Additionally, the robustness analysis, conducted through DOLS and FMOLS, reaffirms the inverse and strong dynamics between economic policy uncertainty and RET, underscoring that policy instability disproportionately affects lower quantiles of RET. The policy implications are threefold. First, Arctic nations must implement stabilized and predictable economic policies to mitigate uncertainty, as fluctuations in economic policy hinder investment in renewable infrastructure. Second, policies should prioritize resource allocation towards clean energy development, ensuring that natural resource wealth is not solely invested into conventional energy sectors but redirected to facilitate RET. Lastly, enhancing environmental technology and governance frameworks through targeted investments and regulatory incentives will further accelerate the transition toward clean energy.National Natural Science Foundation of China, NSFC; Jiangsu University Post-Doctorate Fund; fosters innovative research and academic progres
Direct and indirect acts of labeling gifted pupils in the pro-labeling pedagogical situations
No full textThe labeling gifted pupils is related to the unsparing treatment of the label "gifted" which creates inappropriate teachers' emotions and attitudes towards giftedness. Labeling should be given through "direct acts", which include specific pro-labelled actions and speech toward gifted and can be easily identified and eliminated. However, also the "indirect acts" exist, which are hidden in educational procedures. The study aimed to identify the pro-labeling pedagogical situations and describe the direct and indirect acts of labeling. The qualitative research was conducted in elementary schools in the Czech Republic, with class observations and teacher interviews as data sources. Nine pro-labeling pedagogical situations were identified which were typical with signs such as overemphasizing the differences between gifted pupils, unavailability of activities for other pupils, accentuated selection, and rigidity. The direct acts of labelling included naming gifted pupils by specific names, explicitly expressed instructions for gifted pupils, and presenting increased expectations for their performance. Acts of indirect labeling occurred in situations where the primary purpose was to engage gifted pupil, assemble a group of pupils with a strong performer, quickly activate pupils in competitions, develop the pro-social skills of the gifted, help weaker pupils, assign extra tasks according to recommendations and assess specific tasks for the gifted. The study highlights the existence of indirect acts of labelling next to the direct acts. Limiting the theory of labeling only to direct acts can lead to legitimization and frequent use of inappropriate pro-labeling pedagogical situations against gifted pupils
Valorization of chicken deboner residues: Gelatin extraction and its application for jellies and films
Get PDFIn recent decades, global food industry waste has significantly increased, with food waste categorized into human consumption and non-edible industrial by-products, including animal by-products. This study aims to reduce these by-products by repurposing chicken tissue for gelatin extraction. The gelatin extraction process from mechanically deboned chicken meat residues was optimized using food enzymes, and the physicochemical and rheological properties of the gelatins were analyzed. Temperature and extraction time, as independent factors, were examined using the Taguchi experimental design. Under optimal conditions, the resulting gelatins exhibited high gel strength (196 – 353 Bloom) and viscosity (3.2 – 7.6 mPa·s), making them suitable for gelling agents in jelly confectioneries. Furthermore, low Bloom-value chicken gelatins were used to create edible films, and tests on their sorption and desorption behavior revealed temperature- and humidity-dependent characteristics, with improved plasticity and reduced sorption hysteresis at higher temperatures. This environmentally friendly processing technology for mechanically deboned chicken meat residues aligns with zero-waste principles
Fuelling growth: a qualitative study on the benefits and challenges of growth hacking for micro, small and medium enterprises
No full textPurpose: The rapid expansion of technology has facilitated the widespread adoption of data-driven approaches and strategies for business growth. One such approach is growth hacking (GH), which seeks to optimize growth through experimental methods. Despite increasing use in organizations of all sizes, the academic literature has not fully explored the implementation and potential benefits and challenges associated with GH. This paper aims to address this research gap by providing new insights into GH and categorizing its main benefits and challenges.
Design/methodology/approach: A multiple-case study approach was employed to investigate the growth strategies of micro, small and medium enterprises. Semi-structured interviews were conducted with founders, managers, consultants and professionals in the field.
Findings: The findings shed light on the economic, technological, organizational and managerial benefits derived from GH implementation, which include the scalability of strategies and a data-driven culture, learning from failures, leaner and more efficient processes and improved readiness to respond to change. Several challenges associated with GH implementation were also identified, including entry barriers; limited availability of time, budget and resources and a higher propensity for risk, failure and patience.
Originality/value: This article contributes to the existing literature by providing new evidence on the opportunities and risks associated with GH for better and more effective implementation of this strategy while suggesting future research directions
Environmental footprint of GenAI – Changing technological future or planet climate?
No full textThe beginnings of generative artificial intelligence (GenAI), led by Chat Generative Pre-Trained Transformer (ChatGPT), not only change the behaviour of digital media ecosystem users but also increase the energy consumption of enterprises working with GenAI, which presents them with a fundamental challenge in the era of climate change. This study aims to examine the relationships between the selected aspects of the use of GenAI tools and the environmental perception and behaviour of their users to understand the population's current environmental attitudes towards environmental risks and environmental sustainability. The survey was conducted in October 2024 on a sample of 1,268 respondents of the Czech Republic population. To process the data set, a logistic regression analysis, chi-squared test, Akaike information criterion, and Bayesian information criterion are employed. The results show that the more often people use GenAI tools, the more distant they consider the effects of climate change in time. The low frequency of use of ChatGPT may influence a higher willingness to change popular GenAI tools that are not maintained by environmentally friendly data centres. The frequency of ChatGPT use influences individuals’ perception of the importance of climate-change solving. The more frequently the respondents use artificial intelligence (AI) systems, they less perceive climate change as important. The low frequency of ChatGPT usage is associated with lower willingness to change email provider, transfer own data, leave social networks, stop using a favourite streaming platform and stop using a favourite GenAI platform. The respondents’ attitudes show a visible behavioural change. Internal personal motivation and self-confidence in learning, interest in career and self-confidence when using AI, the behavioural aspects, and the cognitive aspects are altered considerably. Based on the outcomes of the population survey, the study concludes that the issue of environmental friendliness of AI tools should become part of AI literacy that could strengthen population's willingness to use more energy-efficient GenAI platforms. The listed challenges are important in the perspective of the latest technological development, as shown by the discussion on the energy and computational demands of the GenAI platform DeepSeek, which is also discussed in the study.Agentúra na Podporu Výskumu a Vývoja, APVV; Slovenská Akadémia Vied, SAV; Technology Agency of the Czech Republic, TACR, (TQ01000100); Technology Agency of the Czech Republic, TACR; Ministry of Education, Research, Development and Youth of the Slovak Republic, (APVV-21-0188); Vedecká Grantová Agentúra MŠVVaŠ SR a SAV, VEGA, (1/0554/24); Vedecká Grantová Agentúra MŠVVaŠ SR a SAV, VEGATechnology Agency of the Czech Republic within the SIGMA Programme [TQ01000100]; Slovak Research and Development Agency of the Ministry of Education, Research, Development and Youth of the Slovak Republic [APVV-21-0188
Enhancing resource assignment efficiency in service industry: A predict-then-optimize approach with XGBoost
Get PDFThis paper addresses the critical aspect of resource planning in a service context through an integrated predictive and prescriptive approach. Utilizing real-world data from a company providing repair and maintenance services, we demonstrate the use of an XGBoost model to forecast ad-hoc service demands and subsequently optimize resource assignment using a mathematical model. Our findings show that the prediction evaluation metrics significantly improve, highlighting the superiority of complex machine learning models over baseline models such as Linear Regression. Furthermore, the integration of the prediction into the decision-making process resulted in a 26.4% lower decision error compared to the baseline model. Our research also found that the deviations in prediction and optimal objective function values are not aligned. While the average error for MAE % in prediction is 22.2%, the error for the optimal objective function is much lower, reducing to 5.3%. However, although true for our case, this might not be generalizable. Furthermore, when comparing the baseline model with these results, it is also shown that an improvement in prediction accuracy also improves decision making error. Our results indicate that a combined predict-then-optimize approach outperforms the existing methods in both predictive and prescriptive performance, demonstrating its applicability in real-world scenarios
RheoTack evaluation of detaching behavior of silicone-based pressure sensitive adhesives for transdermal therapeutic systems
No full textThis study focuses on applying the RheoTack method to assess the detaching behavior of transdermal therapeutic systems (TTS), which represent skin-applied medications comprising a drug-loaded pressure-sensitive adhesive (PSA) and a flexible backing layer. The RheoTack method provides detailed force-retraction displacement-curves (F-h-curves) that reveal the influence of chemical structure and resin content on PSA deformation and fibril formation. To compare various rod geometries (flat rods with diameters of 5 mm and 8 mm, and a spherically rounded rod with a contact area of 5 mm2), the force-retraction displacement curves were normalized to account for the effective contact areas. The flat and spherical rods led to completely different F-h-curves as well as different failure and tack behaviors. Furthermore, the adhesion formation between the TTS with flexible backing layers and rods during the dwell phase occurs in a different manner compared with rigid plates, particularly for flat rods, where maximum compression stresses occur at the edges and not uniformly over the cross-section. Measurements of F-h-curves were performed with retraction speeds of 0.01, 0.1, and 1 mm/s. The increase in retraction speed increased the stiffness from 250 to 1200 N/m for non-amine-compatible PSA measured with a rod of 8 mm. RheoTack measurements were performed with a dwell time of 1 s, which is consistent with ASTM D2949. However, the TTS was in the adhesion-establishing compression phase for 3 s at 1 mm/s and for 30 s at 0.01 mm/s. Thus, the approach to follow ASTM D2949 has to be reconsidered for testing TTS materials.Graduate Institute Bonn-Rhein-Sieg University of Applied Sciences; Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT, (RP/CPS/2024–2028/005, RP/CPS/05/2024–28); Ministerstvo Školství, Mládeže a Tělovýchovy, MŠMT; Bundesministerium für Bildung und Forschung, BMBF, (03FH039PX5); Bundesministerium für Bildung und Forschung, BMBFGerman Ministry of Education and Research [03FH039PX5]; Ministry of Education, Youth and Sports of the Czech Republic-DKRVO [RP/CPS/05/2024-28