Volume 19 Issue 3

Forest carbon credit project developments throughout the world can contribute to nature-based solutions to mitigate climate change. With Malaysia’s large forest endowment, a study was conducted to evaluate the awareness and knowledge among forest owners, and to identify the main constraints faced when venturing into forest carbon credit projects. A total of 75 companies in both forest plantations and natural forests were involved in the study. The results clearly suggest that knowledge and awareness of forest carbon credit projects is relatively low among forest owners. Hence, forest carbon credit projects development in the country is relatively slow and only a few projects have had serious development to the auction phase. The slow uptake of carbon projects is plagued by the low carbon credit price, lack of clarity in the national carbon policy, limited expertise and capability for project development, and the lack of financing mechanisms for project development. Forest owners prefer biomass production and timber production due to the higher economic returns. Against this background, policymakers as well as federal-state initiatives need to address the gaps with the forest carbon credit project development ecosystem, in order to facilitate and realize the full carbon sequestration potential of the country.

The usability of black pine (Pinus nigra Arnold) in both monitoring the changes in the concentrations of silver (Ag), selenium (Se), antimony (Sb), and thallium (Tl), and in reducing soil or air pollution was investigated. In the study, annual rings of a Pinus nigra tree, cut in 2023 and identified as 356 years old, were grouped into 10-year intervals, and then the changes in these heavy metals throughout the process were determined by analysing the concentrations of these elements. Additionally, the relationship of these elements with other elements was also detected in the scope of the study. The study results suggested that Pinus nigra was not a suitable bio-monitor for monitoring the changes in Ag, Se, Sb, and Tl concentrations in the soil or air, but it was a highly suitable species for phytoremediation studies aimed at reducing the pollution of these elements. Moreover, it was determined that the relationships of the studied elements with essential nutrients, such as Mg, Ca, P, K, Al, Zn, Ni, and Fe, were not statistically significant and were very weak; whereas they exhibited positive and very strong relationships with elements known to be highly harmful for health such as V, Pb, and As.

This study aimed to validate the accuracy of identifying Japanese hardwood species from microscopic cross-sectional images using convolutional neural networks (CNN). The overarching goal is to create a versatile model that can handle microscopic cross-sectional images of wood. To gauge the practical accuracy, a comprehensive database of microscopic images of Japanese hardwood species was provided by the Forest Research and Management Organization. These images, captured from various positions on wood blocks, different trees, and diverse production areas, resulted in substantial intra-species image variation. To assess the effect of data distribution on accuracy, two datasets, D1 and D2, representing a segregated and a non-segregated dataset, respectively—from 1,000 images (20 images from each of the 50 species) were compiled. For D1, distinct images were allocated to the training, validation, and testing sets. However, in D2, the same images were used for both training and testing. Furthermore, the influence of the evaluation methodology on the identification accuracy was investigated by comparing two approaches: patch evaluation and E2 image evaluation. The accuracy of the model for uniformly sized images was approximately 90%, whereas that for variably sized images it was approximately 70%.

Grease-proof paper is an energy-demanding paper product to manufacture, especially during refining and dewatering. Increases in energy efficiency in either stage could result in major savings. This article investigates the potential gains with addition of a stepwise progression vacuum suction box to the forming section during production. For both a lighter, 50 g/m², and a heavier paper grade, 100 g/m², with a pulp-drainability of 86 °SR, a stepwise progression vacuum suction box in four steps would result in increased dryness, simultaneously with decreased energy expenditure. The observed effects were higher for the lower basis weight paper (50 g/m²). Both basis weights experienced clogging of the forming fabric due to the high degree of refining. This adversely affected the dewatering rate, decreasing the amount of air pulled through the paper even when increasing the vacuum pressure. When a stepwise progression suction box in four steps was compared to a single vacuum suction box, there was a 14% increase in dryness for lighter paper, over an equal energy consumption, measured as amount of air pulled through the paper. For the 100 g/m² paper, the increase in dryness was 3% compared to the 50 g/m² paper run over a single vacuum suction box. The results show great promise for energy savings when utilizing stepwise progression suction box dewatering for grease-proof paper production.

Leaf variations of Betula medwediewii in Türkiye with respect to its distribution pattern were studied because this plant taxon is a Euxine element and a distinct relict species in Türkiye. In this context, the aim of this study is to investigate variations in leaf morphological characteristics within and among B. medwediewii populations in natural distribution areas in Türkiye. Thus, the morphological leaf characteristics of four populations of B. medwediewii growing at different elevations spanning from 1472 to 2065 m.a.s.l in two cities (Artvin and Rize) and four boroughs (Arhavi, Borçka, Murgul, and Çamlıhemşin) of Türkiye were analyzed. The four populations were selected based on their natural distribution and 1,200 leaf samples belonging to 40 individuals were measured with ImageJ. According to the results of correlation analysis, statistically significant relationships were determined among morphological leaf characteristics. Mean values for petiole length (1.16 cm), leaf width (5.11 cm), leaf length (7.96 cm), length of lamina (6.79 cm), leaf area (26.62 cm²), leaf vein angle (54.21°), and number of primary leaf veins (20.03) were determined in all populations. Because B. medwediewii contributes to biodiversity and can preserve the ecological stability of the Turkish forest area, its conservation is crucial.

Using renewable steam-exploded poplar (SEP) as carbon source, nickel metal doped carbon hybrid materials were designed to synthesize catalysts (Ni/SEP) with certain oxygen evolution reaction (OER) properties and were compared with nickel catalysts supported on metal organic framework structure (ZIF67-Ni). The roles of SEP support in Ni-based catalyst were considered. Scanning electron microscope (SEM) images confirmed that the fiber could better hinder the aggregation of metal particles. Fourier transform infrared spectroscopy (FT-IR) indicated the presence of surface OH groups after the reduction process. X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) analyses confirmed the major form of metallic Ni in the resulting Ni catalysts. Carbon materials as carriers, the synergetic effect of Ni-doped, and carbon carrier played an important role in facilitating the kinetics of OER, which was similar to the carrier of metal-organic frame material. Notably, the Ni/SEP (11.3 mF/cm^-2) and ZIF67-Ni (37.2 mF/cm^-2) with better OER performance exhibited a smaller double layer capacitances (Cdl), suggesting the intrinsic OER catalytic activity of the Ni/SEP and ZIF67-Ni were much higher in comparison to the ZIF67-Ni/SEP. Moreover, the inferior performance of Ni/SEP further indicated that the synergistic effect between carbon and Ni/NiO contributes to the enhanced OER activity.

The primary aim of this work was to determine the effects of production parameters, such as wood species and timber strength classes, on some mechanical properties of cross-laminated timber (CLT) panels using artificial neural network (ANN) prediction models. Subsequently, using the models obtained from the analyses, the goal was to identify the optimum layer combinations of timber strength classes used in the middle and outer layers that would provide the highest mechanical properties for CLT panels. CLT panels made from spruce and alder timbers, as well as hybrid panels created from combinations of these two wood species, were produced. The strength classes of the timbers were determined non-destructively according to the TS EN 338 (2016) standard using an acoustic testing device. The bending strength and modulus of elasticity values of the CLT panels were determined destructively according to the TS EN 408 (2019) standard. According to ANN results, the optimum timber strength classes and layer combinations were determined for bending strength as C24-C27-C24 for spruce CLT, D18-D24-D18 for alder CLT, C30-D40-C30 and D18-C30-D18 for hybrid panels; and for modulus of elasticity, C22-C27-C22 for spruce, D35-D30-D35 for alder, C16-D24-C16, and D24-C24-D24 for hybrid panels.

The classification of Mortise and Tenon (MT) joints is vital, as it enables standardized terminology, facilitates comparative analysis, and enhances understanding of construction techniques across a variety of applications including the design, manufacturing, and management of wood products. Although the classification of MT joints is crucial, current research in this area lacks a systematic approach. The study adopts a morphological composition paradigm to investigate MT joints. This study introduces a 6-level classification index hierarchy for MT morphology, employing methods from biological classification and arithmetic cross-method coding. By encoding joint features and morphological composition, the study delineates 352 possible joint types and 1056 theoretical compositions across dimensions, elucidating diverse structural logics and aiding comprehension. Next, a feasibility typicality assessment identifies 198 typical and 310 atypical morphological types, presented clearly in graphical form. Validations are conducted through analysis of 2654 research cases, which are encoded according to the index hierarchy, thereby affirming the scientific validity and practical utility of the classification system.

Eutrophication caused by excessive nitrogen and phosphorus is an important factor affecting water quality in drinking water sources. Convenient monitoring of eutrophication in water bodies can reduce the use of pesticides and reduce energy consumption, helping to promote ecological and economic development. This study examined the relationship between water eutrophication and the oxidation-reduction potential (ORP). The results showed that various parameters related to eutrophication, such as ammonia nitrogen, total nitrogen, total phosphorus, chlorophyll-a, and cyanobacteria, had correlations with ORP. There is a close relationship between eutrophication and the concentration of cyanobacteria. When cyanobacteria blooms occur in the drinking water source, it may contaminate the drinking water. Because the conventional eutrophication index does not include the concentration of cyanobacteria, principal component analysis (PCA) was utilized to comprehensively analyze these eutrophication-related parameters and obtain the eutrophication-related index, with the cumulative contribution of principal components reaching 81.8%. Different mathematical methods such as neural network model and mathematical fitting were used to study the relationship between ORP and the eutrophication-related index. A three-segment relationship between the ORP and the index was established. This three-stage relationship was confirmed in different reservoirs.

Flemingia macrophylla has traditionally been applied to relieve inflammation, diabetes, and circulatory complications. The leaf extract of F. macrophylla and its fractions were investigated for their in-vitro antioxidant and anti-diabetic properties. The phytochemical screening showed valuable phytochemicals, including glycosides, flavonoids, saponins, etc. GC‒MS analysis of the phytochemicals in the methanol extract detected 19 bioactive compounds. Among the diverse fractions, the ethyl acetate fraction (EFM) exhibited the highest phenol and flavonoid contents of 557 mg GAE/g and 326 mg QCE/g, respectively. The total antioxidant content of EFM was found to be 292.41±19.16 mg AAE/g, while its antidiabetic study showed the greatest level of α -glucosidase (IC₅₀: 11.27±1.25 µg/mL) and α -amylase (IC₅₀: 10.04±0.63 µg/mL) inhibitory effects. The docking results showed that C6 had the highest binding scores of -9.0, -7.4, and -7.6 kcal/mol against antioxidant (6NGJ), α-glucosidase (5NN5), and α-amylase (4GQR) proteins, respectively. The dynamics simulation disclosed that C6-receptor protein complexes remained stable at the binding pocket under human body conditions and retained their stiff morphology for 100 nanoseconds (ns). ADMET results demonstrated their noncarcinogenic and well-absorbed properties, where PASS prediction data confirmed their efficacy as an antioxidant, antiulcerative, thrombolytic, and antidiabetic. Therefore, F. macrophylla has potential health benefits.