Research Articles

Bamboo can be engineered for laminate boards and other sustainable construction material. The adhesive type is expected to affect the laminated board’s quality. This study analyzed the physical (density, moisture content, and delamination) and mechanical (bending and shear strength) properties of betung (Dendrocalamus asper) bamboo laminated boards prepared using various adhesives. The most favorable adhesive for enhancing betung bamboo laminated boards was determined. The bamboo lamina was arranged into boards (3 layers) measuring 30 x 15 x 1.5 cm each in length, width, and thickness. The laminated board was glued using isocyanate, epoxy, and polyvinyl acetate (PVAc) adhesives using the double glue spread technique. The laminated board was tested for its physical and mechanical properties, following the JAS 234:2003 standard. Betung bamboo laminated board with isocyanate, epoxy, and PVAc adhesives had densities ranging from 0.89 g/cm³ to 0.95 g/cm³, moisture contents of 7.64% to 24.37%, delamination ranges from 0% to 100%, modulus of elasticities from 109,000 to 178,000 kg/cm², modulus of rupture values ​​range from 709 to 1,570 kg/cm², and shear strength values ​​of 25.0 to 60.0 kg/cm². Isocyanate adhesive was found to have the best quality in physical tests, while epoxy adhesive achieved the best quality in mechanical tests of laminated boards.

Roof tiles come in various forms and are crucial to residential construction. A roof tile composite offers the market a selection of superior roof tile products in terms of strength, low density, and environmental friendliness. This research aimed to improve the surface performance and durability of sorghum bagasse-based roof tile composite (SBRTC) through surface coating with natural polymer. Sorghum bagasse was made into roof tile composite using a mixture of molasses and citric acid adhesives (50:50) with a target density of 0.6 g/cm³. Furthermore, the SBRTC surface was coated with tannin–polyurethane at different concentrations (10%, 20%, and 30%), and the results were compared with both uncoated and polyurethane-coated samples. The parameters tested included physical and mechanical properties, surface characteristics, and durability against termite and brown-rot fungi. The result showed increasing density, dimensional stability, mechanical properties, and durability. At the same time, the moisture content decreased. Surface performance exhibits a decrease in the average surface roughness (R_a) value, indicating a smoother surface of roof tile composite after surface coating. Furthermore, a high contact angle, low K-value, and low wettability were achieved. It indicates a more hydrophobic surface. The optimal tannin concentration in the coating solution was 20%.

In today’s competitive market, meeting consumers’ satisfaction and emotional needs is crucial for business success. However, the cognitive gap between designers and consumers often hinders market recognition for bamboo furniture. Therefore, a research framework based on Kansei Engineering (KE) is proposed in this study. First, the emotional needs and related samples were collected, and the sample form was deconstructed systematically. Then, the attribute reduction algorithm in rough set theory was used to extract the key emotional needs that have significant impact on consumer satisfaction. Finally, an intelligent mapping model between product components and emotional needs was constructed using Genetic Algorithm-Backpropagation Neural Networks (GA-BPNN), which predicts the optimal product design parameters that meet users’ emotional needs. Additionally, we conducted an interpretative analysis of the prediction model using the Shapley Additive Explanations (SHAP) method. The evaluation results were significantly higher than the average, validating the advanced and effective nature of the method proposed in this study. Compared with previous KE studies, the GA-BPNN model proposed in this study has better prediction efficiency and higher precision, which can more effectively solve the cognitive differences between designers and consumers. Thus, the development efficiency and decision-making accuracy of enterprises’ product design has been improved.

A comprehensive acoustic analysis was carried out for the huhu, a betelwood instrument from the Jin opera. Techniques included an acoustic visualiser and Fast Fourier Transform (FFT). The harmonic structure, frequency distribution, and timbre quality of the instrument were investigated, focusing on the effect of the use of leather finger cuff on the sound produced. Spectral analyses revealed complex overtones and distinctive spectral patterns for different playing techniques, ranging from 324.47 to 10,277.08 Hz. Finger cuffs significantly altered the harmonic content and timbre. The study utilised high fidelity equipment to conduct multiple recordings under controlled conditions to capture subtle acoustic changes. Statistical analysis of the frequency data revealed a consistent overtone structure, while an acoustic visualiser examined the relationship between playing technique and sound intensity. The analyses emphasised how traditional playing methods (particularly fretting) affect acoustic output. By documenting the current acoustic characteristics of the huhu, this work provides insight into its musical and cultural significance, contributes to the preservation of traditional musical heritage and provides a scientific basis for understanding the unique acoustic characteristics of betel nut wood.

Molded fiber-based packaging has recently surged in popularity as a replacement for single-use plastics (SUPs). However, key challenges include the lack of low-cost, high-yield sustainable fibers that provide adequate strength and moldability while reducing drying energy consumption, which is essential for widespread adoption. Therefore, this study explores high-yield, sustainable fiber development for molded packaging applications through carbonate and bicarbonate pulping, as well as oxygen delignification. Furthermore, it examines mild refining and cationic starch treatments to balance strength and drainage properties during the molding process. Results show that carbonate and bicarbonate pulping of sugarcane bagasse achieved yields of approximately 72%, while oxygen delignification reduced yield by 2% but improves mechanical performance by 25%. Mild refining decreased dryness by 10%, whereas adding 1% cationic starch enhanced dryness by 9% and increased mechanical strength by up to 60%. These alternative fibers from sugarcane bagasse present a viable solution for replacing SUP packaging, helping to mitigate pollution and reduce waste accumulation.

This study examined the response of color information in digital wheat canopy images from Shandong Province, China, to meteorological indicators during extreme cold spells. Analysis revealed that low-temperature stress altered pixel color and grayscale values, with shifts captured by skewness and kurtosis parameters of color gradation distributions. The kurtosis and skewness of color gradient distributions showed the strongest sensitivity to cold stress. Daily minimum temperature was significantly correlated with kurtosis values for R (0.661), G (0.744), B (0.694), and grayscale (0.744) channels. Models relating these parameters to meteorological factors were developed, with polynomial functions outperforming multilinear approaches. All models demonstrated satisfactory fit, as evidenced by determination coefficients exceeding 0.480. The kurtosis model for green values achieved exceptional prediction accuracy, surpassing 90%. Findings demonstrate quantifiable cold-induced changes in canopy color gradient distribution, establishing a foundation for enhancing freeze damage monitoring systems through image-based metrics. These models enable efficient early warning by linking meteorological data to visible canopy responses, offering practical tools for mitigating agricultural cold stress impacts.

Current algorithms for surface defect detection in particleboard often encounter limitations such as high computational complexity and excessive parameter scale. To address these challenges, this study proposes the LE-YOLO model, which incorporates a normalized Wasserstein distance into the loss function to enhance the detection capability for minute surface defects. A dynamic mixed convolutional network module is introduced to construct a lightweight backbone architecture. Moreover, the Shared Dilated Feature Pyramid (SDFP) module is employed in the neck network, effectively reducing computational overhead while preserving detection accuracy. A lightweight detection head was further designed, integrating shared convolutional operations with a distribution-aware loss function, thereby substantially improving detection performance in complex textured environments. Experimental evaluations conducted on the Chipboardv1.0 particleboard surface defect dataset demonstrated that compared to the baseline YOLOv11n model, LE-YOLO achieved a 5% improvement in recall, a 1% increase in F1 score, a 4% enhancement in mAP@50, a 6% gain in mAP@50–95, a 12.69% acceleration in inference speed, and an 18.6% reduction in parameter count. Compared with other models, the proposed approach not only improved detection precision but also effectively reduced model complexity, achieving a lightweight and efficient detection framework.

Ag-TiO₂/EVA composites were synthesized using silver-loaded nano TiO₂ (Ag-TiO₂) and ethylene-vinyl acetate (EVA) emulsion as raw materials, aiming to develop functional materials with antibacterial, anti-mold, and anti-discoloration in properties for wood protection. The study systematically evaluated the composites’ inhibition efficacy against discoloration fungi and molds, long-term antibacterial performance, as well as the tensile strength and water vapor transmission rate of composite films. Experimental results demonstrated that 100% inhibition efficacy against Botryodiplodia theobromae and Aspergillus niger was achieved under two optimal conditions: film thickness of 0.12 to 0.15 mm with Ag-TiO₂ loading ≥20%, or film thickness of 0.18 to 0.21 mm with Ag-TiO₂ loading ≥15%. Samples with 10%, 15%, and 20% Ag-TiO₂ loading exhibited >99.99% antibacterial rates against both Escherichia coli and Staphylococcus aureus. Notably, the 20% Ag-TiO₂ sample retained high antibacterial values of 93.0% and 91.7% against these bacteria after 15 days of storage. Mechanical and barrier property tests revealed that compared to the control, the tensile strength of composite films increased by 19.8%, 24.6%, and 29.3% at Ag-TiO₂ loadings of 10%, 15%, and 20% respectively, while water vapor transmission rates decreased by 48.6%, 52.9%, and 60.6%. These findings collectively confirm that Ag-TiO₂/EVA composites possess excellent bactericidal effects and significant wood anti-mold/anti-discoloration functionality.

China’s abundant low-rank coal faces challenges in utilization due to high moisture content and low calorific value. Microbial biodegradation has emerged as a promising method to improve coal quality. This study investigates the coal-degrading capabilities of the Bacillus amyloliquefaciens strain, designated as strain N7 in this study. Experimental results demonstrated that strain N7 significantly degraded lignite. On Luria-Bertani solid medium, the strain formed clear coal solubilization zones, indicating its biodegradation potential. Three-dimensional excitation-emission matrix fluorescence spectroscopy revealed humic-like substances, suggesting humic acid formation through oxidative depolymerization. Enzyme assays identified lignin peroxidase (LiP) and lipase as key contributors, with LiP showing particularly high activity. Scanning electron microscopy showed dense bacterial colonization on coal surfaces, implying efficient biodegradation through direct interaction. Fourier-transform infrared spectroscopy and X-ray photoelectron spectroscopy indicated an increase in free hydroxyl groups in degraded coal, supporting structural breakdown. Degradation products analysis revealed 32% phenolic compounds and 55% long-chain alkanes, providing chemical evidence of lignite decomposition. These results highlight strain N7 as an effective microorganism for lignite biodegradation, offering insights for optimizing microbial coal bioconversion.

Butterfly pea flower (BPF) powder, which is rich in bioactive compounds, was evaluated for the impact of various drying methods on its solubility, physical properties, and chemical composition. Four drying methods were used: thermal drying at 50 °C, 60 °C, 70 °C, and natural sun drying. The powders were assessed for solubility time, hygroscopicity, density, flowability, and chemical stability using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infrared (FTIR). Solubility times ranged from 148 to 162 s, with no significant differences. The 70 °C dried sample (Sample C) had the fastest dissolution rate and highest hygroscopicity. Total phenolic and anthocyanin contents increased with temperature, peaking in sun-dried samples (Sample D). Density measurements showed Sample C had the highest bulk density and optimal flowability, while Sample D had superior water holding capacity. The SEM analysis revealed morphological differences, with Sample A showing a smooth surface and Sample C exhibiting significant particle disintegration. The XRD analysis showed that Sample C had the highest crystallinity. The FTIR analysis confirmed the stability of key functional groups, with sun-dried samples retaining phenolic compounds. These findings suggest drying methods can optimize BPF powder’s properties, enhancing its bioactivity for health applications.