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Publications - 6674

Comparison between European protestant and catholic economic development through modern painting

Balassa Bernadett

Publication Name: Deturope

Publication Date: 2018-01-01

Volume: 10

Issue: 1

Page Range: 82-96

Description:

Since Max Weber, economists suggest that religious activity affects the European economic development, and this hypothesis was proven between the seventeenth and nineteenth centuries. Accordingly Protestant economic thinking accelerated the evolving system of capitalism, giving adequate attitudes to the accumulation of wealth. This research supposes that the mentioned capitalist approaches have their own impressions on visual arts, particularly on modern painting. It examines almost nine hundred religious paintings from the fifteenth to nineteenth centuries, investigating signs of business activities on the artworks. This form of qualitative examination apply the methodology of content analysis. As a result of the study the former hypothesis of Weber could be verified from multidisciplinary approach.

Open Access: Yes

DOI: 10.32725/det.2018.005

Mechanical, Durability and Microstructural Performance of OPC–GGBFS–FGD Gypsum Ternary Concrete: Identification of an Operational Sulfate Activation Threshold

Prahlad Prasad Anasuya Sahu Sanjay Kumar Ardalan B. Hussein Pramod Kumar Anand Bhatt

Publication Name: Materials

Publication Date: 2026-07-01

Volume: 19

Issue: 14

Page Range: Unknown

Description:

Ordinary Portland cement (OPC) production contributes approximately 7–8% of global anthropogenic CO2 emissions, driving urgent demand for clinker-efficient binders utilizing industrial by-products. Flue gas desulfurization (FGD) gypsum and ground granulated blast-furnace slag (GGBFS) represent underutilized industrial by-products with documented potential as supplementary cementitious materials. This study investigates the mechanical, durability and microstructural performance of OPC–GGBFS–FGD gypsum ternary concrete mixtures incorporating untreated flue gas desulfurization (FGD) gypsum at 0–20% of total binder mass and ground granulated blast-furnace slag (GGBFS) at 25–50% of total binder mass in M30 structural concrete (w/b = 0.45). Compressive, split tensile and flexural strengths were evaluated at 7–90 days alongside rapid chloride penetration (RCPT), water absorption, strength efficiency index (SEI) and SEM–EDX analyses. Binary GGBFS replacement progressively enhanced long-term compressive strength, with T35F0 attaining 55.6 N/mm2 at 90 days (+33.7% relative to the OPC control). Moderate FGD gypsum contents (5–10%) further enhanced overall performance. Among all mixtures, T50F10 exhibited the best overall performance on the mechanical and durability indicators evaluated, achieving 54.2 N/mm2 compressive strength at 90 days together with a rapid chloride permeability value of 410 C, corresponding to ‘Very Low’ chloride ion penetrability. Beyond 10% FGD gypsum, progressive multi-parameter deterioration was observed, and mixtures containing 20% FGD gypsum failed to meet the M30 design requirement at 28 days. SEM–EDX confirmed that optimum sulfate activation produced a dense C–(A)–S–H-rich matrix, while excess sulfate caused matrix disruption. The findings establish 10% FGD gypsum by total binder mass as the optimum sulfate activation threshold for the investigated GGBFS and FGD gypsum sources at w/b = 0.45, and demonstrate the potential of untreated industrial FGD gypsum to produce durable, low-clinker structural concrete.

Open Access: Yes

DOI: 10.3390/ma19142962

Impact of process gases on wettability and adhesive bond strength of laser- treated DC01 steel and plasma-treated polypropylene surfaces

Eszter Kókai

Publication Name: Journal of Adhesion

Publication Date: 2025-01-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

This study investigates how different process gases (air, argon, and nitrogen) influence the wettability and adhesive bond strength of DC01 steel and polypropylene surfaces treated by laser and plasma methods. The aim was to clarify how gas composition and processing parameters affect surface activation and whether contact angle measurements alone can explain adhesive performance. On DC01 steel, laser treatment significantly reduced water contact angles, achieving full wetting at specific power and scanning speeds. However, lap shear testing showed that a 0° contact angle did not always result in the same bond strengths. Argon-treated samples consistently provided the highest shear strength. For polypropylene, plasma activation improved both wettability and bonding. Nitrogen plasma lowered contact angles from 63° on untreated surfaces to 14° at 200 mm/min and 9° at 400 mm/min, producing the strongest joints. This study is one of the first to systematically compare the effects of different gases on metals and polymers, linking wettability and mechanical testing to offer practical guidance for optimizing process parameters for strong and reliable adhesive joints.

Open Access: Yes

DOI: 10.1080/00218464.2025.2595302

Sustainable and cost-effective optimal design of steel structures by minimizing cutting trim losses

Marco Domaneschi R. M. Movahedi Raffaele Cucuzza Giuseppe Carlo Marano

Publication Name: Automation in Construction

Publication Date: 2024-11-01

Volume: 167

Issue: Unknown

Page Range: Unknown

Description:

Since the beginning of the structural optimization field, the optimal design was characterized by the least-weight configuration. In this sense, all the researchers agreed on adopting the minimum-weight optimization statement as the most promising approach to achieve an optimized employment of material. However, especially for steel structures, this approach completely fails the primary goal of encouraging standardization of pieces during the production phase. Except for rare cases, increasing diversity among structural elements leads to a dramatic increase in the financial cost as well as the environmental impact of the structure because of the material waste generated during the cutting procedure. In this paper, a real-coded Genetic Algorithm has been adopted and the well-known one-dimensional Bin Packing Problem has been implemented within the structural optimization process. The Objective Function formulation lies in a marked change of the paradigm in which the target function is represented by the amount of steel required by the factory instead of the structural cost (e.g. weight). The proposed approach is tested on different steel structures moving from 2D truss beams to 3D domes. Addressing the optimal stock of existing elements leads to a significant waste reduction of 40% in almost all the investigated case studies.

Open Access: Yes

DOI: 10.1016/j.autcon.2024.105724

Remarks on the location theories of startups: A case study on the Visegrad countries

Agnieszka Skala Petra Kinga Kézai

Publication Name: Regional Science Policy and Practice

Publication Date: 2024-09-01

Volume: 16

Issue: 9

Page Range: Unknown

Description:

Startups, understood as new forms of innovative and fast-growth ventures, are emerging in traditional industries, creating intense competition and displacing former leaders. Our study focuses on location theory embedded in institutional and resource context and its application to startups in the Visegrad countries. We know a lot about the location choices made by small and medium-sized enterprises (SMEs). However, research on the location preferences of startups is limited, especially within the transition economies of Central and Eastern Europe. We investigated the differences in location decisions between startups and SMEs and those between startups located in metropolitan areas and rural areas. A study on the location decisions of startups was conducted in 2021 using mixed methods. The research showed that local factors strongly influence startups. It may seem obvious that large cities provide startups with access to resources, markets and support through the local innovation ecosystem. However, our analysis identified three significant differences between startups and traditional SMEs regarding location choice. For startups, the availability of skilled workforce and an R&D center/research university is more difficult. In contrast, local (family) ties and rootedness are more important for rural startups than metropolitan ones. This study provides new evidence on how spatial externalities affect innovative startups in the Visegrad countries and identifies factors that influence the location of startups in urban and rural areas, with a particular focus on Hungarian startups. For the latter, the study shows that state aid to startups has an ambiguous effect on the shape of the ecosystem, producing contradictory effects on the development of startups in the region. Given the methodological limitations described in our paper, further research is advisable to deepen the study of localization theory in the context of startups in the CEE region, especially in the V4 counties.

Open Access: Yes

DOI: 10.1016/j.rspp.2024.100063

Optical Rail Surface Crack Detection Method Based on Semantic Segmentation Replacement for Magnetic Particle Inspection

Szabolcs Fischer Mykola Sysyn Olga Nabochenko Jianxing Liu Lei Kou

Publication Name: Sensors

Publication Date: 2022-11-01

Volume: 22

Issue: 21

Page Range: Unknown

Description:

Railway damage detection is of great significance in ensuring railway safety. The cracks on the rail surface play a key role in studying the formation and development process of rail damage, predicting the occurrence of rail defects, and then improving the service life of the rail. However, due to the small shape of the cracks, the typical detection method is relatively complicated, and the speed is quite slow. Although traditional magnetic particle inspection technology is fairly accurate at detection, it is costly and inconvenient to carry and install, while also limiting the detection speed and affecting the system’s operation. In this paper, a semantic segmentation detection method is developed by using various collected rail surface crack data and deep learning through a neural network. By comparing the inspection of the same rail surface with magnetic particle inspection technology, only inexpensive cameras are used and the inspection speed is increased while maintaining relatively high accuracy. In addition, the method can achieve fast detection speeds if it is extended to be combined with high-frequency cameras. It is an economical, efficient, and environmentally friendly method for future rail surface detection.

Open Access: Yes

DOI: 10.3390/s22218214

Assessing Local Site-Specific Response Spectra Based on Site Data in Gyor

Orsolya Kegyes-Brassai Benjamin Labar

Publication Name: Advances in Transdisciplinary Engineering

Publication Date: 2024-01-01

Volume: 59

Issue: Unknown

Page Range: 422-430

Description:

It is essential to understand seismic ground motion in order to understand how dynamically a structure responds to earthquakes. Due to variations in seismic loading, strong ground vibrations can damage structures to varying degrees. The different essential traits of powerful ground motions help explain this ground diversity during moderate to large earthquakes. This study mainly focuses on the comparison between ground motion parameters such as the Peak Ground acceleration (PGA), and local site spectra considering the design response spectrum and site-specific response spectra of varying soil profiles in Gyor. Multichannel analysis of Surface Waves (MASW) data from eleven different places in Gyor were considered and analyzed using the 1-dimensional response analysis software, STRATA, and a detailed comparison was carried out between the different site locations in terms of PGA, and local site spectra. The result revealed the sites with the highest amplifications based on peak ground values of acceleration, velocity, and displacements. With 1-dimensional STRATA software, peak ground acceleration profiles, and response spectrum results are obtained and compared to Eurocode 8 standards.

Open Access: Yes

DOI: 10.3233/ATDE240575

Understanding the psychology of knowledge sharing and experience in digital service ecosystems

Ankit Mehrotra Attila Kurucz Rsha Alghafes Nidhi Sahore Jaskirat Singh Rai

Publication Name: Acta Psychologica

Publication Date: 2026-07-01

Volume: 267

Issue: Unknown

Page Range: Unknown

Description:

Drawing on service-dominant (SD) logic, which conceptualizes value as emerging through resource integration and use rather than direct technological outputs, the study examines how technology-mediated knowledge-sharing platforms (TMKSP) influence employee and employee-perceived customer experience using the DART (dialogue, access, risk assessment, transparency) framework of value co-creation. Employing a mixed-method approach, a pre-hoc qualitative study (Study A) identified key TMKSP features relevant to value co-creation, which informed the development of a DART-based survey for the quantitative phase (Study B). Data from retail employees were analyzed using PLS-SEM with two-tailed bias-correct bootstrapping. The findings show that TMKSP significantly improves employee experience via platform access and reduced perceived risk, while enhancing employee-perceived customer experience through employee-customer dialogue and platform transparency. Mediation analysis confirms the explanatory role of DART-based constructs in linking TMKSP with experience outcomes, although the mediating role of perceived platform risk was not supported. The study contributes theoretically by operationalizing SD logic within an internal service ecosystem and demonstrating how value-in-use is shared through employee-perceived co-creation conditions rather than through direct technological effects. It offers practical guidance for managers aiming to design employee and customer-centric knowledge-sharing ecosystems.

Open Access: Yes

DOI: 10.1016/j.actpsy.2026.106974

Beyond Forecast Accuracy: Evaluating the Error–Profit Paradox in AI-Based Copper Price Prediction

Tibor Bareith László Vancsura Tatay Tibor

Publication Name: Machine Learning and Knowledge Extraction

Publication Date: 2026-07-01

Volume: 8

Issue: 7

Page Range: Unknown

Description:

Copper is a strategically important commodity whose price dynamics are increasingly affected by structural changes, geopolitical shocks, and the global energy transition. These conditions create substantial challenges for forecasting models and provide a useful setting for evaluating the practical value of machine learning predictions. This study compares statistical and artificial intelligence-based forecasting models for copper price prediction under different market regimes and structural break conditions. Model performance is assessed using a multi-dimensional evaluation framework that combines statistical accuracy (MAPE), dynamic pattern reproduction (Taylor diagrams and time-lagged cross-correlation analysis), and the economic performance of forecast-driven trading strategies. The results reveal a consistent error–profit paradox: models with the highest statistical forecasting accuracy do not necessarily generate the best trading outcomes. In several cases, models with larger prediction errors achieve superior economic performance because they capture directional market dynamics more effectively. The analyses further show that structural breaks substantially alter model rankings and predictive usefulness, highlighting the importance of regime-aware evaluation. These findings suggest that forecast accuracy alone provides an incomplete assessment of model quality in financial and commodity forecasting applications. The study contributes to machine learning evaluation research by proposing an integrated framework that jointly considers predictive accuracy, temporal dynamics, model robustness, and economic utility, thereby offering a more comprehensive approach to assessing forecasting systems in real-world decision-making environments.

Open Access: Yes

DOI: 10.3390/make8070209