This study investigated modifying casein adhesives to improve their moisture resistance and elasticity for use in the wood industry. Six different formulations were tested, including pure casein adhesive, polyvinyl acetate (PVAc) adhesive, and mixtures of the two, as well as modifications involving abietic acid, borax, and diethyl phthalate. While the modified casein adhesives met the minimum requirements according to DIN EN 205, they did not match the performance of the unmodified casein adhesive. Although the modified adhesives performed worse than the unmodified variants, they still demonstrate the potential for sustainable use of non-marketable milk as a source of raw materials.
The tree-of-heaven (Ailanthus altissima (Mill.) Swingle) is one of the most aggressive arboreal invaders, threatening forest health and biodiversity across five continents. Given its rapid spread, severe ecological impact, and management difficulty, this paper (i) synthesises current knowledge of ecological factors driving its invasion in forest settings, (ii) critically evaluates available control methods, and (iii) proposes an integrated, evidence-based management framework suitable for forest ecosystems. Prevention strategies, such as legislation, vigilant monitoring, and the rapid removal of female trees, are essential first-line defences. For control, systemic herbicides applied via foliar sprays, basal bark, cut-stump, or stem injection methods provide the most effective long-term suppression. In contrast, mechanical or physical treatments alone often result in vigorous resprouting. Biological control agents show potential but remain purely experimental. However, the absence of approved biological agents and the limited availability of long-term cost-effectiveness data currently constrain management planning and large-scale implementation in forest ecosystems. This review presents a decision matrix that links control options to tree ontogenetic stages and site conditions, highlighting research needs that balance effectiveness, costs, and ecological safety. Overall, this synthesis offers a clear, evidence-based toolkit for managers and policymakers managing A. altissima in forest ecosystems.
DWC (Deep Wood Classifier) is a hybrid method that aims to achieve high accuracy and efficiency in wood species classification by combining deep learning and classical machine learning algorithms. In this method, convolutional neural network (CNN) models such as EfficientNetV2B3, Xception, and InceptionResNetV2 are optimised and trained to classify wood species. The accuracy rate is further improved when the features extracted from these deep learning models are classified with classical machine learning algorithms. The combination of EfficientNetV2B3 and SVC provides fast and effective classification with 99.56% accuracy, while Xception and Logistic Regression achieved the highest success with 99.69% accuracy. The DWC method exhibited excellent results in confusion matrix and ROC curve analyses, providing higher accuracy and more efficient training processes compared to existing methods in the literature. The combination of deep learning and classical machine learning algorithms has made DWC stand out with its high accuracy rates and fast training times. This hybrid approach offers a significant innovation in wood species classification, demonstrating superior performance compared to other methods in the field.
This study concerned the possibility of enhancing the outdoor performance and thermal properties of wood-plastic composites (WPCs) by incorporating nanoparticles (NPs). Titanium dioxide (TiO2) NPs were selected, being one of the most commonly used types, and were added to the matrix in concentrations up to 10%. Their addition improved the mechanical properties of WPCs due to the strong interaction between TiO2 and the composite components. Furthermore, the good reflectivity properties of TiO2 improved the surface color stability of WPCs. Even under intensive UV light exposure, the surface color changes in WPCs containing TiO2 were moderate compared with the control samples. Microscopic analysis indicated that TiO2 NPs significantly reduced crack formation. Although surface erosion was not completely inhibited, it was reduced. The condensation cycle of weathering weakened the bonds between the wood and polymer, leading to mechanical losses. Scanning electron microscopy (SEM) images revealed micro-cracks, which explained the decreased values obtained for the mechanical properties of reinforced WPCs. However, the decrease was limited to 0.46% for composites containing 5% TiO2. The TiO2 NPs also acted as a thermal barrier, retarding thermal degradation, which occurred more moderately than in the controls. Additionally, the fire performance of reinforced WPCs was enhanced by TiO2 NPs, which improved char formation and increased the limit oxygen index (LOI) values to 25.9% O2.
The natural frequency of a building is one of the main parameters affecting the dynamic and acoustic properties of the building. This study investigates the influence of two timber ceiling technologies-KVH timber and the Steico wall system-on the dynamic and acoustic properties of prefabricated timber-frame buildings. KVH is a kiln-dried, finger-jointed solid structural timber widely used in load-bearing applications, whereas the Steico wall system is a prefabricated lightweight timber panel designed for sustainable construction. Also, this paper aims to study the effect of the presence of an additional story on the dynamic and acoustic properties of timber buildings. Three different timber buildings have been taken into account. The first one is a two-story building with a KVH layer, the second one is a one-story building with a Steico wall, and the third one is a one-story building with a KVH layer. Measured fundamental natural frequencies were 42.63 Hz, 26.81 Hz, and 21.39 Hz, respectively, demonstrating clear quantitative differences between the systems. Statistical indicators, including mean values, standard deviation, and coefficients of variation (below 15%), confirm acceptable repeatability. The stiffness of those buildings has been evaluated as well. It was concluded from this study that the ceilings composed of the KVH layer have better acoustic properties than the ceilings composed of the Steico wall. Also, it was concluded that the presence of an additional story worsens the acoustic properties of the ceiling and increases the stiffness of the building, affecting the dynamic properties of the timber building.
