Volume 20 Issue 4

Anaerobic digestion (AD) is a widely recognized method for converting organic waste into biogas, offering a sustainable solution for both waste management and renewable energy generation. This review critically examines recent advancements in mathematical modeling and machine learning (ML) approaches applied to biogas production from AD processes. The study categorizes the models into daily and cumulative biogas production models, kinetic models, and hybrid AI-based predictive techniques. Special attention is given to the comparative evaluation of first-order kinetics, modified Gompertz, and Chen-Hashimoto models, highlighting their applicability and limitations. Furthermore, the integration of artificial neural networks (ANNs) and other ML algorithms is discussed in the context of optimizing biogas yield, understanding system dynamics, and reducing operational uncertainties. Research gaps are identified, including the need for more robust hybrid models, real-time monitoring systems, and studies under diverse feedstock and environmental conditions. The review emphasizes that combining traditional modeling with intelligent systems offers a powerful approach to enhancing AD performance and scaling sustainable energy solutions.

The phin is a lute that originated in Thailand’s Isan region. The strings 1, 2, and 3 for the phin is E4, A3, and E3. It was tuned to the key of G major.  The strings 1, 2, and 3 running notes are E4, F4, F4#, G4, A4, B4, C5, D5, E5, F5, G5, A5, B5, C6, D6, and E6; A3, A3#, B3, C4, D4, E4, F4, G4, A4, A4#, C5, D5, E5, F5, G5, and A5; and E3, F3, F3#, G3, A3, B3, C4, D4, E4, F4, G4, A4, B4, C5, and D5, respectively. The keys F4#, B3, and F3# appear in the first octave only from strings 1, 2, and 3, respectively. In this study, the sound was analyzed with a PicoScope oscilloscope and Adobe Audition. The equation for the polynomial (i.e., the fret number versus the partial frequency) for open strings 1, 2, and 3 is y_string1 = 3.14x² + 9.10x + 316.07, y_string2 = 2.15x² + 5.51x + 214.55, and y_string3 = 1.51x² + 6.53x + 146.24. The changes in frequency (the multiplication factor of the x²) increased gradually with the pitch. Strings 3 (E3), 2 (A3), and 1 (E4) showed the multiplication factor of 1.51, 2.15, and 3.14.

To explore the effects of support stiffness and grinding media shape on the superfine grinding performance of wheat bran, a vibration grinding platform with adjustable support stiffness (25 to 55 kN/m) was used for tests with stainless steel spherical grinding media (SGM) and cylindrical grinding media (CGM), respectively. The results showed that both factors significantly affected the grinding effect. When stiffness exceeded 35 kN/m, micro powder quality and yield improved for both media. Below 35 kN/m, SGM’s micro powder quality deteriorated, while CGM’s micro powder quality peaked at 30 kN/m. At 30 kN/m, fine powder, micro powder, and superfine powder yields reached their maximum for both media. The mass fraction of superfine powder was 52.9% for CGM, and that of SGM was 29.3% higher than at 35 kN/m. SGM consistently produced better particle size distribution than CGM, with the smallest median particle size (D₅₀) difference (21.5%) at 30 kN/m. The superfine yield of CGM was not always higher than that of SGM. Their mass fraction difference showed a quadratic nonlinear relationship. A coupling effect between media shape and stiffness was found to determine grinding performance. Overall, this work provides a basis for optimizing the superfine grinding performance of wheat bran in vibration mills.

The aim of this work was to assess the suitability of selected methods of surface treatment on X48CrMoV8-1-1 tool steel for application on chipping knives in wood-chipping machines. Three material surface conditions of X48CrMoV8-1-1 tool steel were evaluated for their tribological scratching behavior. The first surface condition was related to the conventionally machined chipping knife from the manufacturer without surface treatment. The second condition involved plasma nitriding treatment, and the third was a PVD-coated surface with “CROSAL ® Plus” (AlCrN based) coating. Several complementary analyses were carried out, namely microstructural observations, nano-indentation measurements, and tribological scratch tests. From the scratch tests, friction coefficients depending on applied load were determined. The best nano-indentation results were obtained for the PVD-coated surface, namely 23.7 ± 1.6 GPa for nanohardness and 270.3 ± 19.0 GPa for elasticity modulus. The best results of tribological and scratching behavior were obtained for the plasma-nitrided surface, namely 0.34 ± 0.21 for coefficient of friction and 1.88 ´ 10^-6 mm³/N.m for specific wear rate. Based on the obtained results of laboratory tests, it can be concluded that the plasma-nitrided surface of X48CrMoV8-1-1 tool steel can ensure its better tribological performance compared to other investigated material conditions.

Video Abstract

The togunggak is a traditional musical instrument made of bamboo. This work observed the unique sound characteristics to define the notes using Fast Fourier Transform (FFT) via a picoscope. The sound characteristics are represented by the dominant frequency with the corresponding intensity. The note of the biggest (tog. 6) to the smallest (tog. 1) bamboo tube is recorded as from G3 to G4. This work reveals that tog. 2 to tog. 5 for togunggak A produce the notes E4, D4, B3, and A3, which is not similar to togunggak B, i.e., E4, D4, C4, Bb3. All bamboo tubes produced fundamental frequency with the presence of two lower partials at 100 Hz and 200 Hz and weaker overtones (except tog. 6)  in their frequency spectrum. Using symbol S for semitone dan T for tone (i.e. 2 semitone), the note interval of the tog. 6 to tog. 1 can be presented as TT2TT2T i.e., the G3, A3, B3, D4, E4, G4 note interval are presented by G3-A3 as T, A3-B3 as T, B3-D4 as 2T, D4-E4 as T and E4-G4 as 2T. The time frequency analysis (TFA) displays all the spectrograms with distinct prominent fundamental frequency peak.

The rapid growth of e-commerce platforms presents unique opportunities to analyze consumer behavior and predict product preferences in the furniture industry. This study explores the use of machine learning techniques to predict consumer choices for furniture products based on favorite listing data from e-commerce platforms. A dataset of 239 furniture products was collected, categorized into three groups: most preferred, moderately preferred, and least preferred. Key attributes, including furniture type, dimensions (width, depth, height), color, material, and price, were analyzed. Machine learning models, specifically Decision Trees and Random Forests, were applied to develop prediction models for these categories. The models were assessed using metrics such as accuracy, precision, sensitivity, and F1-score. Results indicated that the Random Forest model outperformed the Decision Tree, achieving 83% accuracy in predicting preference categories. Feature importance analysis highlighted that price and physical dimensions were the most significant factors influencing consumer preferences. These findings suggest that practical and economic aspects are prioritized over aesthetic features when choosing furniture. The study demonstrates the potential of machine learning in predicting consumer behavior, offering valuable insights for manufacturers and retailers in optimizing product development, inventory management, and marketing strategies.

Although chemical fertilizers increase plant growth and crop yields, their usage over a long period harms soil health, damages the beneficial microorganisms, and reduces soil fertility. Therefore, there is interest in using natural biostimulants in agriculture instead of chemical fertilizers. This study aimed to examine how spraying with zinc (ZnO) and boron (B₂O₃) oxides, as well as the biostimulants yeast extract (YE) and seaweed extract (SWE), and their combinations affect the yield and fruit quality of Barhi date palm. The trees were sprayed four times starting from mid of February with one month between each two sprays with 50 mg/L ZnO + 50 mg/L B₂O₃; 100 mg/L ZnO + 100 mg/L B₂O₃; 0.2% or 0.4% YE; 0.2% or 0.4% SWE; 50 mg/L ZnO + 50 mg/L B₂O₃ + 0.2 % YE + 0.2 % SWE, (combination 1); 100 mg/L ZnO + 100 mg/L B₂O₃ + 0.4% YE + 0.4% SWE (combination 2) compared to not-treated trees. The results indicated that applying ZnO and B₂O₃, YE and SWE either individually or in combination effectively enhanced the productivity and fruit quality of the date palm cv. Barhi compared to the control. The results also showed that the combined application gave a larger improvement in the measured parameters, particularly combination 2, which was the best treatment, followed by combination 1.

The objective of this work was to enhance fire and decay resistance of wood materials using environmentally friendly and non-toxic wood preservatives. Two copper-based impregnation agents, Korasit KS and Tanalith-E, were applied to Scots pine (Pinus sylvestris L.) specimens. The fire performance was evaluated with ASTM E69 (2002) by measuring mass loss after fire exposure. Decay resistance was assessed according to EN 113 (2006), using white-rot fungus Trametes versicolor and brown-rot fungus Postia placenta over a 12-week incubation period. Specimens treated with 9% concentration of Korasit KS exhibited the lowest mass loss after fire exposure. Similarly, increasing the concentrations of both preservatives resulted in reduced mass loss under fire conditions. Data were statistically analyzed using one-way ANOVA and Duncan’s test (α = 0.05). Specimens impregnated with 9% Tanalith-E showed the lowest mass loss and the highest resistance to both T. versicolor and P. placenta. Overall, it is recommended that wood materials intended for industrial applications be impregnated with higher concentrations of Korasit KS to improve fire resistance, and with Tanalith-E to enhance biological durability against fungal decay.

To address the growing demand for sustainable, functional, and culturally aesthetic outdoor leisure chairs while enhancing their emotional and cultural significance, this study proposes a design strategy that integrates Kansei engineering with parametric derivation. Plant patterns derived from traditional Chinese artifacts were selected as the research subject, and their types and structural characteristics were systematically classified to construct a representative pattern library. The semantic differential method was employed to evaluate perceptual images and identify patterns consistent with the aesthetic values of outdoor furniture. By using parametric software, the shape of the pattern is simplified into functional holes, achieving lightweight and heat dissipation functions. Two conceptual designs for outdoor leisure chairs were realized using bio-based materials, resulting in reduced material use. The proposed designs were assessed using fuzzy evaluation methods, which yielded high satisfaction scores and validated the feasibility and effectiveness of the approach.

With the increasing emphasis on green home furnishing and ecological environment, reconstituted decorative thin wood is being used more widely as a new material with excellent performance and beautiful appearance. This paper discusses applying the color theory of reconstituted decorative thin wood from the perspective of green ecology. First, academic achievements are summarized related to reconstituted decorative thin wood and its color theory, exploring its research direction and future development trends. Secondly, this paper outlines the classical color system and theory, at the same time, based on the K-means algorithm, color extraction of reconstituted decorative thin wood samples, and establishes the color relationship network model. Using the basic theory and design method of prototype typology, the texture types of reconstituted decorative thin wood are classified, and the texture characteristics and texture composition of reconstituted artistic modeling thin wood are studied. Through data analysis of 96 questionnaires and summarizing and analyzing the results of the respondents’ perceived preferences for the experimental samples, the feasibility of the restructured decorative thin wood design scheme was verified based on the CNCSCOLOR color palette theory of color matching design. Then the degree of choice and the degree of willingness to purchase of the restructured decorative thin wood scheme and its application of the customized closet effect were evaluated through the Likert Scale.