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Would really long-only climate-transition strategies in commodities bring lower market risk for sustainable markets in the long run? The Islamic sustainable market versus the global sustainability leaders

Laszlo Vasa Mohammad Nasr Isfahani Mahdi Ghaemi Asl Diling Xiang

Publication Name: Economic Analysis and Policy

Publication Date: 2024-06-01

Volume: 82

Issue: Unknown

Page Range: 1271-1295

Description:

By allocating investments towards commodities that align with climate-transition goals, environmentally conscious commodity investment strategies serve to promote and support sustainable markets, channeling capital towards sectors that prioritize environmental sustainability. Through the application of a quantile causality test, which examines the relationship between commodity-based strategies with a climate-transition focus and eco-friendly markets, over the period spanning from May 1, 2013, to May 25, 2023, our findings reveal a bi-directional causality relationship between different themes of sustainable markets and long-only climate-transition strategies in the commodity market across various market conditions. Furthermore, employing a quantile time-frequency connectedness approach allows us to discern that long-only climate-transition strategies in the commodity market exhibit lower long-run total connectedness with responsible and conscious markets compared to the short term. Consequently, these results suggest that transition-oriented strategies for commodities in a climate-conscious world not only mitigate market risk for regenerative markets in the long run but also indicate that different types of global sustainability leaders demonstrate a stronger connectedness with climate-transition strategies in commodities when compared to the Islamic sustainable market across a majority of quantiles and time horizons. In light of these findings, policymakers are urged to prioritize the long-term dimensions of climate-transition strategies in commodity markets by implementing new emission standards and environmental benchmarks. Additionally, the design and implementation of similar long-only climate-transition strategies in other markets would further enhance the long-term effectiveness of climate-conscious markets and foster stronger connections with responsible markets. our study underscores the significance of integrating climate-transition strategies into commodity markets and highlights their role in promoting sustainable and environmentally conscious investment practices. By directing investments towards climate-aligned commodities, policymakers and market participants can contribute to the long-term sustainability of global markets while fostering stronger connections between sustainable markets and climate-transition strategies in commodities.

Open Access: Yes

DOI: 10.1016/j.eap.2024.05.012

Evaluation of Antibacterial Properties of Commercial Essential Oils on Foodborne Pathogens in a Liver Pâté-Type Product

E. Lakatos V. Kapcsándi Babett Greff Miklós Posgay

Publication Name: Chemical Engineering Transactions

Publication Date: 2023-01-01

Volume: 107

Issue: Unknown

Page Range: 253-258

Description:

In the past, several efforts have been made to find suitable substitutes for synthetic preservatives in meat products with fewer side effects on human health. Essential oils have gained worldwide interest due to their antimicrobial activity. The addition of these aromatic compounds to foods may be hampered by their strong sensory characteristics (taste and smell). The objective of this study was to evaluate the efficiency of five essential oils (EOs) (Ocimum basilicum L., Origanum vulgare L., Rosmarinus officinalis L., Salvia officinalis L., and Thymus vulgaris L.) against important foodborne pathogens. First, a microdilution assay was carried out to determine the minimal inhibitory concentration (MIC) of the EOs against Staphylococcus (Staph.) aureus ATCC 6538, Salmonella (S.) enterica subsp. enterica serovar Typhimurium ATCC 14028, and Escherichia (E.) coli ATCC 25922. Since the EOs inhibited the growth of these bacteria, their activity was studied in a real food matrix. The in vivo test was performed on the model of liver pâté: the homogenized and heat-treated samples were formulated with EOs at concentrations of 1 MIC and 2 MIC, inoculated with bacterial suspensions (105 CFU/g), packaged under vacuum, and stored at 4 ºC for 3 days. The addition of 2 MIC of thyme and sage oils showed a significant reduction in the viable counts of E. coli, S. Typhimurium, and Staph. aureus compared to the control samples. Overall, this study demonstrated that thyme and sage EOs, as natural preservatives, had great potential to prevent the growth of important foodborne pathogens (E. coli, S. Typhimurium, and Staph. aureus) in liver pâté, but their efficiency was highly dose-dependent. However, the tested concentrations of EOs (1 MIC and 2 MIC) had an influence on the sensory characteristics of the finished products that may hinder their future applicability to improve the shelf-life of meat products. Therefore, further studies are required to clarify such an issue.

Open Access: Yes

DOI: 10.3303/CET23107043

Mamdani-type inference in fuzzy signature based rule bases

No authors available

Publication Name: 8th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2007

Publication Date: 2007-12-01

Volume:

Issue:

Page Range: 513-525

Description:

The concept of fuzzy signatures might be useful when modeling complex, well structured problems, where one or several components of the structure are determined at a higher level by a sub-tree of other components. The data set belonging to the problem has an arbitrary structure, from which the structure of the data may slightly differ. An aggregation operator is given for each node, for the purpose of modifying the structure, so that data with missing components can be evaluated. Deducing a conclusion from an observation having such a structure is a key issue. In this paper fuzzy signature based rule bases will be introduced, then the generalisation of the well known Mamdani method for signature based rules will be shown step-by-step. Finally, an example of inference on fuzzy signatures will be discussed.

Open Access: No

DOI: DOI not available

Exploiting the functional training approach in takagi-sugeno neuro-fuzzy systems

Pedro M. Ferreira Cristiano L. Cabrita António E. Ruano Laszlo T. Koczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2013-01-01

Volume: 195 AISC

Issue: Unknown

Page Range: 543-559

Description:

When used for function approximation purposes, neural networks and neuro-fuzzy systems belong to a class of models whose parameters can be separated into linear and nonlinear, according to their influence in the model output. This concept of parameter separability can also be applied when the training problem is formulated as the minimization of the integral of the (functional) squared error, over the input domain. Using this approach, the computation of the derivatives involves terms that are dependent only on the model and the input domain, and terms which are the projection of the target function on the basis functions and on their derivatives with respect to the nonlinear parameters, over the input domain. These later terms can be numerically computed with the data. The use of the functional approach is introduced here for Takagi-Sugeno models. An example shows that this approach obtains better results than the standard, discrete technique, as the performance surface employed is more similar to the one obtained with the function underlying the data. In some cases, as shown in the example, a complete analytical solution can be found. © 2013 Springer-Verlag Berlin Heidelberg.

Open Access: Yes

DOI: 10.1007/978-3-642-33941-7_48

Scalable collaborative filtering approaches for large reeommender systems

Bottyan Nemeth Istvan Pilaszy Gabor Takacs Domonkos Tikk

Publication Name: Journal of Machine Learning Research

Publication Date: 2009-01-01

Volume: 10

Issue: Unknown

Page Range: 623-656

Description:

The collaborative filtering (CF) using known user ratings of items has proved to be effective for predicting user preferences in item selection. This thriving subfield of machine learning became popular in the late 1990s with the spread of online services that use recommender systems, such as Amazon, Yahoo! Music, and Netflix. CF approaches are usually designed to work on very large data sets. Therefore the scalability of the methods is crucial. In this work, we propose various scalable solutions that are validated against the Netflix Prize data set, currently the largest publicly available collection. First, we propose various matrix factorization (MF) based techniques. Second, a neighbor correction method for MF is outlined, which alloys the global perspective of MF and the localized property of neighbor based approaches efficiently. In the experimentation section, we first report on some implementation issues, and we suggest on how parameter optimization can be performed efficiently for MFs. We then show that the proposed scalable approaches compare favorably with existing ones in terms of prediction accuracy and/or required training time. Finally, we report on some experiments performed on MovieLens and Jester data sets.

Open Access: Yes

DOI: DOI not available

Context dependent reconstructive communication

Tamás D. Gedeon Laszlo T. Koczy

Publication Name: Isciii 07 3rd International Symposium on Computational Intelligence and Intelligent Informatics Proceedings

Publication Date: 2007-09-25

Volume: Unknown

Issue: Unknown

Page Range: 13-19

Description:

No description provided

Open Access: Yes

DOI: 10.1109/ISCIII.2007.367354

Conformal cooling with heat-conducting inserts by direct metal laser sintering

István Hatos B. Kocsis Hajnalka Hargitai

Publication Name: Iop Conference Series Materials Science and Engineering

Publication Date: 2018-11-30

Volume: 448

Issue: 1

Page Range: Unknown

Description:

With the development of layer manufacturing technologies injection mold inserts with conformal cooling channels can be manufactured. If the cooling channels can be placed along the geometry, the heat removal is uniform and effective. In tight mold regions, formation of cooling channel is not possible or not efficient. The combination of conformal cooling and heat conductive insert can be an ideal solution for the effective cooling.

Open Access: Yes

DOI: 10.1088/1757-899X/448/1/012027

Impact of Traffic Sign Diversity on Autonomous Vehicles A Literature Review

Csaba Koren Ziyad N. Aldoski

Publication Name: Periodica Polytechnica Transportation Engineering

Publication Date: 2023-01-01

Volume: 51

Issue: 4

Page Range: 338-350

Description:

Traffic sign classification is indispensable for road traffic systems, including automated ones. There is a fundamental difference in the visual appearance of traffic signs from one country to another. Each dataset has its design standards and regulations based on shape, color, and information content, making implementing classification and recognition techniques more difficult. This paper aims to assess the influence of traffic sign diversity on autonomous vehicles (AVs) by reviewing several previous studies, comparing, summarizing their results, and focusing on classifying and detecting traffic sign datasets based on color, shape, and deep learning spaces using various methods and applications. Furthermore, it covers the main challenges facing road designers and planners considering changes to road safety infrastructure. It will be argued that compiling and standardizing a comprehensive global database of traffic signs is very difficult because it is costly and complex in application. However, it is still one of the possible solutions for the coming decades. Recommendations for future developments are also presented in this study.

Open Access: Yes

DOI: 10.3311/PPtr.21484

Effect of pH, Carbonate and Clay Content on Magnesium Measurement Methods on Hungarian Soils

Csaba Centeri Renato Kalocsai Márton Vona Zsolt Biró Viktoria Vona Tamás Szakál István Mihály Kulmány Sándor Zsebő Lajos Kubina Zsolt Giczi

Publication Name: Soil Systems

Publication Date: 2024-06-01

Volume: 8

Issue: 2

Page Range: Unknown

Description:

More exact information on soil nutrient management is crucial due to environmental protection, nature conservation, decreasing sources for mining, general precaution, etc. Soil magnesium (Mg) analytical methods of potassium chloride (KCl), Mehlich 3 (M3), water (WA) and cobalt hexamine (CoHex) extractions are compared with an elemental analysis and X-ray fluorescence (XRF) analysis. The ratio of the available to the total Mg content was calculated and compared on the whole dataset. The results showed that the linear regressions between all the pairs of Mg content measurement methods were significant. The linear relationship between the KCl and CoHex methods has the highest determination coefficient (R2 = 0.96), followed by WA–M3 (R2 = 0.68), M3–CoHex (R2 = 0.66) and M3–KCl (R2 = 0.60). The M3 solution demonstrated a greater capacity for extracting Mg from the soil. The second part is the analysis of the influence of CaCO3, pH, soil texture and clay content on the measurable magnesium content of soils. It was established that the extraction methods, the soil and the classification method of the soil properties affect the evaluation. These results may help through the nutrient replenishment and the melioration of soils. These results can help the examination of mineral nutrients, especially the Mg uptake.

Open Access: Yes

DOI: 10.3390/soilsystems8020049