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Publications - 6374

Classification of flours based on color measurements and evaluation using multivariate mathematical methods

Ferenc Kajdi András Horváth Ottó Dóka

Publication Name: Heliyon

Publication Date: 2025-11-01

Volume: 11

Issue: 16

Page Range: Unknown

Description:

The quality of flour and its composition are essential questions for bakeries and customers. In this study, 44 different cereals were studied with colorimetry. The color indices CIE L∗, a∗ and b∗ along with the reflection spectra were measured and evaluated using multivariate statistical methods. Principal Component Analysis (PCA) and Non-Negative Matrix Factorization (NMF) were applied to characterize reflection functions and reduce the dimensionality of these data. The aim of the study was to determine whether color measurements could differentiate between whole-grain and non-whole-grain flours, and between wheat and non-wheat (triticale and rye) flours. Cluster analysis was performed on the reflection spectral data, L∗a∗b∗ coordinates, PCA coefficients, and NMF weights to identify distinct sample groups. Both dimensionality reduction methods revealed that the wheat samples studied form a four-dimensional subspace in the original multidimensional reflection spectra dataset. Furthermore, the findings confirmed that the applied methods effectively distinguish whole grain from non-whole grain flours and wheat from non-wheat flours.

Open Access: Yes

DOI: 10.1016/j.heliyon.2025.e44096

Wedelolactone Inhibits Hepatitis B Virus Replication by Modulating NF-κB and Nrf2/HO-1 Signaling: An in-vitro Huh7 1.3-mer HBV Plasmid Model

U. Saeed Xuehui Bu Z. Z. Piracha Di Xiao Bin Wang

Publication Name: Iranian Journal of Pharmaceutical Research

Publication Date: 2026-12-01

Volume: 25

Issue: 1

Page Range: Unknown

Description:

Background: Chronic hepatitis B virus (HBV) infection is a well-recognized cause of hepatic injury through prolonged viral replication, inflammation, and oxidative stress. Existing antiviral drugs limit viral replication but cannot eliminate viral transcription or even totally preclude liver injury, thus reemphasizing the significance of drugs with combined antiviral and hepatoprotective effects. Objectives: To evaluate the effects of wedelolactone on HBV replication, gene expression, inflammation, and oxidative stress in an in-vitro model of HBV plasmid transfection with human hepatic cells. Methods: Human hepatocellular carcinoma cells (Huh7) were transfected with a 1.3-mer plasmid and treated with wedelolactone (2.5 - 10 µM). Luciferase assays for HBV promoter activity, Northern blotting and Southern blotting for transcripts and replicative intermediates, qPCR for extracellular HBV DNA, and western blotting for viral antigens such as HBx were performed. Cell cytotoxicity was measured. NF-κB/IκB, inflammatory cytokines (TNF-α, IL-6), and antioxidant markers (Nrf2, HO-1, Keap1) were assessed to evaluate inflammatory and oxidative responses. Results: Wedelolactone significantly suppresses HBV promoter activity, RNAs, core particle formation, and extracellular HBV DNA. It reduced the expression of HBcAg and HBsAg. It inhibited NF-κB activation and cytokine release, while simultaneously enhancing Nrf2/HO-1 signaling, including induction of heme oxygenase-1 by lowering levels of Keap1. Conclusions: Wedelolactone exerts dual antiviral and hepatoprotective actions by inhibiting HBV replication and modulating inflammatory and oxidative stress pathways.

Open Access: Yes

DOI: 10.5812/ijpr-168329

Genetic and Bacterial Programming for B-Spline Neural Networks Design

János Botzheim Cristiano L. Cabrita António E. Ruano Laszlo T. Koczy

Publication Name: Journal of Advanced Computational Intelligence and Intelligent Informatics

Publication Date: 2007-03-01

Volume: 11

Issue: 2

Page Range: 220-231

Description:

The design phase of B-spline neural networks is a highly computationally complex task. Existent heuristics have been found to be highly dependent on the initial conditions employed. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this paper, the Bacterial Programming approach is presented, which is based on the replication of the microbial evolution phenomenon. This technique produces an efficient topology search, obtaining additionally more consistent solutions.

Open Access: Yes

DOI: 10.20965/jaciii.2007.p0220

Review of materials used for ballast reinforcement

Majd Ahmad

Publication Name: Acta Technica Jaurinensis

Publication Date: 2021-08-25

Volume: 14

Issue: 3

Page Range: 315-338

Description:

This mini review summarizes the most recent research in ballast reinforcement. Several materials are being used for the purpose of improving the ballast layer in railways, including geosynthetics, rubber sheets and binding agents. Such methods of reinforcement have proven to be beneficial for increasing the strength, stiffness, and resilience of the ballast layer in addition to reducing settlement, breakage, degradation, and maintenance cost and frequency. Latest studies try to find the best types, placement, and combination of geosynthetics to achieve the highest strength and resistance, in addition to obtaining the optimum percentage of binding agents and methods of applying them in order to discover the most effective binder that achieves the most improvement to the mechanical properties of the layer for a reasonable price. An overview of the recent tests conducted to study the reinforced ballast layer and their results is presented in this paper, as well as an overall evaluation of the implementation of these reinforcement methods in railways.

Open Access: Yes

DOI: 10.14513/actatechjaur.00610

Investigation of the impact of a solar panel system installed on an heavy-duty truck trailer on fuel consumption at the ZalaZONE test track

András Háry Gergő Sütheö Leticia Pekk Richárd Peszleg

Publication Name: Advances in Science and Technology Research Journal

Publication Date: 2025-01-01

Volume: 19

Issue: 4

Page Range: 304-310

Description:

This study evaluates the impact of a solar panel system installed on a heavy-duty truck (HDV) trailer on fuel consumption, tested at the ZalaZONE track. Two vehicles were assessed – diesel-powered and an liquefied natural gas (LNG) powered truck, with the latter equipped with solar panels. Over five days, the solar system powered cabin electronics, reducing idle time and fuel use. While fuel and carbon dioxide (CO₂) savings were observed, performance was limited by battery charge and sunlight exposure. The results show potential for up to 10% fuel savings, demonstrating the system’s feasibility for reducing emissions in long-haul transport, though further optimization is needed.

Open Access: Yes

DOI: 10.12913/22998624/200029

Issues about autonomous cars

Claudiu Radu Pozna Csaba Antonya

Publication Name: Saci 2016 11th IEEE International Symposium on Applied Computational Intelligence and Informatics Proceedings

Publication Date: 2016-07-07

Volume: Unknown

Issue: Unknown

Page Range: 13-18

Description:

The Autonomous car is a complex topic, different technical fields like: Automotive engineering, Control engineering, Informatics, Artificial Intelligence etc. are involved in solving the human driver replacement with an artificial (agent) driver. The problem is even more complicated because usually, nowadays, having and driving a car defines our lifestyle. This means that the mentioned (major) transformation is also a cultural issue. The paper will start with the mentioned cultural aspects related to a self-driving car and will continue with the big picture of the system.

Open Access: Yes

DOI: 10.1109/SACI.2016.7507360

Chinese and Indian FDI in Hungary and the role of Eastern Opening policy

Eszter Lukács Katalin Völgyi

Publication Name: Asia Europe Journal

Publication Date: 2021-06-01

Volume: 19

Issue: 2

Page Range: 167-187

Description:

The aim of this paper is to assess the main features of Chinese and Indian investments in Hungary and the role of the Hungarian Government’s Eastern Opening policy in the attraction of investments from these two Asian giants. This paper covers the sectoral distribution, modes of market entry, and motivations of Chinese and Indian foreign direct investments. The automotive sector is the most attractive sector for investors from both countries. ICT manufacturing (electronics) and services, and the renewable energy sector are also very attractive for Chinese companies. The same is true for IT/BPO services and the chemical sector in the case of Indian companies. Chinese and Indian companies enter the Hungarian economy mainly through green-field investments or acquisitions. Market-seeking and strategic asset-seeking motives are dominant in the case of investors from both countries. This paper also puts a special emphasis on studying the impacts of Hungary’s Eastern Opening policy (launched in 2012) on Chinese and Indian investments. The findings show that the Eastern Opening policy has had a significant impact on the investment decision (location choice) of new Chinese and Indian investors and further expansion of investments by Chinese and Indian companies located in Hungary due to four factors, namely high-ranking political meetings, strategic cooperation agreements, cash grants from the Hungarian Government and supportive services of HIPA.

Open Access: Yes

DOI: 10.1007/s10308-020-00592-1

Crude oil Price forecasting: Leveraging machine learning for global economic stability

Gagan Deep Sharma Aviral Tiwari Mohammad Razib Hossain Amar Rao Dhairya Dev

Publication Name: Technological Forecasting and Social Change

Publication Date: 2025-07-01

Volume: 216

Issue: Unknown

Page Range: Unknown

Description:

The volatility of the energy market, particularly crude oil, significantly impacts macroeconomic indices, such as inflation, economic growth, currency exchange rates, and trade balances. Accurate crude oil price forecasting is crucial to risk management and global economic stability. This study examines various models, including GARCH (1,1), Vanilla LSTM, GARCH (1,1) LSTM, and GARCH (1,1) GRU, to predict Brent crude oil prices using different time frequencies and sample periods. The LSTM and GARCH (1,1)-GRU hybrid models showed superior performance, with LSTM slightly better in predictive accuracy and GARCH (1,1)-GRU in minimizing squared errors. These findings emphasize the importance of precise crude oil price forecasting for the global energy market and manufacturing sectors that rely on crude oil prices. Accurate forecasting helps ensure economic sustainability and stability and prevents disruptions to production and distribution chains in both developed and emerging economies. Policymakers may choose to implement energy security measures in response to the significant impact of crude oil price volatility on the macroeconomic indicators. These measures could include maintaining strategic reserves, diversifying energy sources, and decreasing the dependence on volatile oil markets. By doing so, a country's ability to handle oil price fluctuations and ensure a stable energy supply can be enhanced.

Open Access: Yes

DOI: 10.1016/j.techfore.2025.124133

Elasto-plastic truss optimization under geometric nonlinearity using a genetic algorithm

Pálma Porrogi Majid Movahedi Rad Péter Grubits

Publication Name: Fracture and Structural Integrity

Publication Date: 2026-01-01

Volume: 20

Issue: 75

Page Range: 124-156

Description:

No description provided

Open Access: Yes

DOI: 10.3221/IGF-ESIS.75.10