Analecta Technica Szegedinensia

To Buy or Not To Buy?

Edina Lendvai — 2025-12-28

As the world evolves, marketing is gaining ground and its role in our lives is becoming more and more crucial. The result is a set of influences on our consumer behaviour, which can change our attitudes and buying habits. In most cases, companies are able to achieve this without our knowledge, with the aim of increasing their purchasing power. In our research, we wanted to achieve our goal by using a quantitative method, i.e. we wanted to get to know the habits of the participating consumers and to obtain information about the behaviour of the respondents. We have used an online questionnaire (by 322 answerers) to investigate the psychological and environmental factors that influence our decisions. The aim of manufacturers is to use promotional tools to manipulate our emotions to create a request in consumers, which creates a demand, and thus a product that is not very useful. In our research we investigated how much the mood of shoppers influences their choices and decisions. We found that even conscious shoppers often make purchases according to their mood, sometimes even for unnecessary products.

Our main achievements:

- Conscious consumers buy far fewer products they do not need than non-conscious consumers

- Using as many emotions as possible in the design of advertising can lead companies to success, because those who can be influenced often rely on their emotions to make decisions.

- The mood of the supermarkets today plays a crucial role in influencing consumers.

EDCST: Enhanced Density-Aware Cross-Scale Transformer for Robust Object Classification under Atmospheric Fog Conditions

Fiston Oshasha — 2025-12-28

Atmospheric fog poses a critical challenge for computer vision systems in autonomous driving, surveillance, and robotics, where reliable object classification is essential. Under severe fog, classification accuracy can degrade by over 50%, and most existing approaches rely on separate defogging steps, which limit their applicability in real-time settings. This study introduces the Enhanced Density-Aware Cross-Scale Transformer (EDCST), a novel architecture designed for direct object classification under foggy conditions without requiring prior defogging. To support model training and evaluation, we developed a physics-based simulation framework generating four fog types (uniform, gradient, patchy, and adaptive) across nine intensity levels. EDCST leverages 384 dimensional embeddings, eight transformer layers, and twelve attention heads, trained using curriculum learning and OneCycleLR scheduling. On CODaN-Fog (15,500 images at 224×224 resolution), EDCST achieves 84.4% accuracy on clean images and retains 74.2% accuracy under severe fog (80% intensity), outperforming baseline transformers by 15.8%. Class-wise sensitivity analysis reveals that larger objects, such as vehicles and animals, maintain over 75% classification performance, while smaller objects are more affected. Patchy fog causes the greatest accuracy drop (19.1%), followed by adaptive (8.9%) and uniform fog (6.8%). The model converges in 100 epochs within 513 minutes. This work introduces a real-time-capable classification framework that eliminates defogging requirements and maintains strong performance under diverse fog conditions, making it highly suitable for safety-critical vision applications.

Examination of Wines from the Csongrád Wine Region and Monitoring of Fermentation

Blanka Juhász — 2025-12-28

The focus of our research was on two different grape and wine varieties from the Csongrád Wine Region. In the first part of our research, we examined wines of various strains and vintages made using oxidative and reductive techniques. Based on our results, differences in content were identifiable between vintages and between oxidative and reductive techniques, even samples were from the same cultivation site. In the second part of our research, we monitored the fermentation of wines in progress, applying various examination methods. The aim of our research was to gather information on the changes occurring during the fermentation. As the fermentation period progressed, the value of the dielectric constant continuously increased, which was related to the change in alcohol content. Based on our findings, fermentation monitoring based on the dielectric constant could be a well-applicable, chemical-free, and quickly executable method.

Dietary Interventions in Neurodegenerative Diseases

Ünkan Urganci — 2025-12-28

Neurological disorders represent one of the most considerable global health challenges—affecting approximately one in three people over their lifetimes. As of 2021, ≈ 43% of the global population were living with some form of neurological condition, including stroke, migraine, dementia, and neurodegenerative disorders. Diseases such as Alzheimer's disease, Huntington’s disease, Parkinson's disease, and amyotrophic lateral sclerosis pose significant challenges, as the global population ages. While these conditions are influenced by multifactorial interactions, dietary factors play a crucial role in their onset and progression. Studies show that adherence to the Mediterranean and ketogenic diets along with the supplementation of antioxidants and certain vitamins, can improve memory and cognitive function. The impacts of diet are evidenced by the outcomes of behavioral tests, particularly those assessing motor and cognitive functions, as well as through histopathological and immunohistochemical analyses that indicate the protection of neurons. Further studies have analyzed mechanisms through dietary components modulate oxidative stress, neuroinflammation, iron management in cells, and various signaling pathways. Crucially, understanding the mechanisms of these components is vital for supporting their dietary inclusion in neuroprotective strategies and pinpointing new therapeutic targets in the treatment of neurodegenerative diseases. In this review, the therapeutic mechanisms of diet are discussed in-depth.

Intensification and Monitoring of Anaerobic Fermentation of Sewage Sludge from the Meat Industry

Zsófia Gréta Sánta — 2025-12-28

Anaerobic digestion is a complex process, and the right quality of feedstock is essential for its proper completion. Although, meat industry wastewater is not ideal feedstock for biogas production, its properties can be improved by pre-treatments. In our chosen pre-treatments, we added magnetite nanoparticles to the sludge and then irradiated it with microwaves at different power levels. Monitoring the fermentation is crucial, especially in industrial practice. We monitored the progress by measuring the dielectric properties of the sludge samples. Our results show that dielectric measurements are a promising alternative for monitoring the anaerobic fermentation because there is a clear correlation between the changes in the value of the dielectric constant and the progression of the fermentation. Our results also clearly support the positive effect of the chosen pretreatments on the amount of biogas produced during fermentation. While the amount of gas increased, the methane content of the biogas produced did not change as verified by gas analysis.