Volume 20 Issue 4

In the important coastal marsh wetland ecosystem, the soil organic carbon content is subject to multiple environmental factors in Yancheng. The research objectives were to explore the effects of sampling time, soil depth, and vegetation types on soil organic carbon content by screening the core data of related literature and analyzing with the descriptive statistics, Kendall’s consistency test, Spearman’s Rank correlation, and principal component analysis (PCA). The analysis showed that the effects of the factors on soil organic carbon content were significantly different. The plant growth was vigorous, resulting in relatively high soil organic carbon content (80 to 50 t/ha·yr), especially in the spring and summer seasons. In addition, the organic carbon content of the topsoil (0 to 20 cm) was significantly higher than that of the soil at depths below 20 cm, showing higher levels (20 to 50 t/ha·yr). Among different vegetation types, the carbon storage capacity of Spartina alterniflora showed superior performance compared to other vegetation (10 to 25 t/ha·yr). The results provide a scientific basis for the assessment and protection of the carbon storage function of wetlands, intending to promote the sustainable management of wetland ecosystems.

A machine learning (ML)-based framework was developed for predicting and optimizing the antioxidant activity of Ainsliaea acerifolia water extracts. while the response surface methodology (RSM) is deficient in modeling nonlinear interactions. In this study, three machine learning (ML) algorithms, Extreme Gradient Boosting (XGB), Random Forest (RF), and Support Vector Machine (SVM), were evaluated using extraction variables (temperature, time, and solvent-to-solid ratio) along with flavonoid and polyphenol content as input features. Among the models evaluated, the XGB model showed the most advanced antioxidant prediction capabilities, as evidenced by its R² of 0.9835 and RMSE of 2.52 on the test data set. The biological significance of the features was explored using SHAP analysis, revealing flavonoid content and extraction temperature as key contributors. A graphical user interface (GUI) was developed to facilitate real-time prediction, enhancing accessibility for researchers and industrial users. This approach improves operational efficiency by optimizing extraction conditions, predicting antioxidant activity from data including flavonoids and polyphenols, and reducing reagent usage. This study highlights the potential of ML as a sustainable alternative for natural product optimization and lays the groundwork for future research that integrates bioactivity prediction with formulation design.

Defense mechanisms were studied for Pinus brutia, a cornerstone Turkish forest tree, against pine processionary moth damage by Thaumetopoea pityocampa (Den. & Schiff.) and Thaumetopoea wilkinsoni Tams 1926 moth species. This research addressed the significance of Pinus brutia in afforestation and breeding. The expression of enzymatic antioxidants (SOD, POD, CAT, APX) and photosynthetic pigments (chlorophylls and carotenoids) at a clonal level in response to insect damage was assessed. Approximately 84 needle samples from 28 Pinus brutia clones from the Antalya Düzlerçamı Brutian Pine Seed Orchard were studied. Samples were collected in February and August 2021 to capture responses during key insect activity periods. These samples were then analyzed for pigment concentrations and antioxidant activities. Statistical analysis revealed that sampling period and clone significantly affected chlorophyll and carotenoid levels. The POD and SOD activities were primarily influenced by the sampling period. However, CAT activity was affected by the number of insect pouches, the period, and the clone. APX activity was significantly impacted by both pouch number and sampling period. These findings offer insights into how seasonal changes and genetic variations modulate P. brutia clones’ defense mechanisms against pine processionary moth infestations, informing future forest management.

Copper oxide (CuO) nanoparticles were prepared using waste-derived cellulose from bamboo biomass as a functional additive. The cellulose, recovered from an alkaline dissolution process, enhanced the dispersion and structural integrity of CuO nanoparticles (NPs). The CuO prepared in the presence of waste cellulose (CuO-C) exhibited a specific surface area of 32 m²/g, compared to 7 m²/g for pure CuO. Scanning electron microscopy (SEM) revealed a feather-like CuO structure influenced by the presence of the waste-derived cellulose matrix. The catalytic activity of CuO-C was tested through the reduction of 4-nitrophenol (4-NP) to 4-aminophenol (4-AP), achieving complete conversion within 15 min. The synthesis cost of CuO-C was approximately RM 3.30 per gram. Antibacterial tests confirmed activity against both Staphylococcus aureus and Klebsiella pneumoniae. These findings demonstrate the feasibility of using a highly alkaline solution from the cellulose dissolution process to produce low-cost CuO with improved catalytic and antibacterial properties.

The usability of wood-based smart furniture interfaces for elderly users remains a critical challenge in aging-in-place solutions. This study aims to explore the most effective visual presentation styles of sofa illustrations in the smart sofa mobile app interface, with the goal of reducing cognitive load and enhancing the interaction experience for elderly users. To achieve this, we evaluated the cognitive responses of elderly users to different visual presentation styles through eye-tracking experiments and correctness analysis. As the results show, the four visual presentation styles exhibited comparable attention levels but diverged in concentration patterns. A 3D modeling schematic focused on peripheral interface areas, whereas physical product schematic and planar schematic emphasized hardware components. Abstract styles increased cognitive resource allocation and prolonged information processing. Pupil diameter and time to first fix (TTFF) data indicated that the 3D schematic imposed the lowest cognitive difficulty and pressure, while physical product schematic and 3D modeling schematic provided superior real-time feedback clarity. Therefore, wood-based smart sofa interface design should address elderly users’ needs by optimizing visual presentation styles, reducing cognitive load and stress, and improving attention. Future research should explore multi-channel human-computer interaction to support smart sofa adoption for aging in place.

Sustainable composites were produced by recycling polystyrene (PS) and pine and poplar fiber residues remaining after lignin extraction. Polystyrene was dissolved in acetone and reinforced with wood fiber residues at 10%, 20% and 30%. The mixture was dried at 100 °C for 2 hr, granulated, and pressed at 190 °C under 5 MPa for 20 minutes. Characterizations of samples were performed according to physical (ASTM D1037 for water resistance and ASTM 7032-21 for density measurement), mechanical (ASTM D638 for tensile, ASTM D790 for flexural), scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) analyses. The addition of fiber residue increased (up to 6.7%) the density but decreased the water absorption (WA) (up to 22%) and thickness swelling (TSW) (up to 12%). Fiber residue increased tensile strength (TS) by 46 to 167% and flexural strength (FS) by 45 to 82%. However, it decreased tensile modulus (TM) by 0 to 58% and flexural modulus (FM) by 3 to 12% (excluding pine). However, pine fiber residue increased FM by 2 to 19%. SEM analyses revealed homogeneous distribution of fiber residues.

Evidence by which to confirm the location and approximate manufacturing date of document paper is a critical task in forensic investigations, particularly in cases involving suspected forgery or document manipulation. In this study, periodic marks formed during the papermaking process were analyzed using light-transmitted images captured by a two-dimensional lab formation sensor. Step and angle data from the top five intensity peaks were extracted and used to train tree-based classification models. To handle directional symmetry, a modulo 180° transformation was applied to the angle data. The random forest (RF) classifier outperformed decision tree (DT) and extreme gradient boosting (XGB) models, achieving the highest F1 score. Feature importance analysis revealed that the step and angle at the third intensity level were the most discriminative features, likely reflecting structural characteristics of forming fabrics or drainage patterns. A simplified univariate strategy using these features also showed potential for estimating production periods. However, differences between the top and bottom surfaces—particularly in twin-wire systems—introduced classification bias, highlighting the need to separately classify paper sides in forensic datasets. Overall, this study demonstrates the feasibility and limitations of using periodic mark analysis for document dating.

This study investigates the crucial role of sodium sulfate in pulp washing liquors and its impact on the reattachment of lignin to pulp fibres during the brownstock washing process. The dissolution of lignin during washing and its potential redeposition onto the pulp fibres is influenced by various factors. Three distinct types of pulp – unbleached, bleached, and cotton linters – were used to explore these effects. The washing experiments were conducted using industrial wash liquor and were repeated further with the addition of sodium sulfate. The resulting products of the washing process, including the liquor discharge and the washed pulp, were thoroughly evaluated. Analytical techniques, such as UV measurements of lignin content in the liquor discharge and characterization of the pulp, were employed to assess the outcomes. The findings reveal that the addition of sodium sulfate to the washing liquor results in an increase in its conductivity and ionic strength. Moreover, it was observed that lignin reattachment to pulp fibres was significantly greater when washing was performed with sodium sulfate addition. Among the pulp studied, unbleached kraft pulp exhibited the highest degree of lignin reattachment, followed by bleached kraft pulp, with cotton linters showing the least.

The influence of the temperature of the paper pulp and drying of towel papers containing polyamidoamine-epichlorohydrin (PAE – 3.5 mg/g ADM) on their wet tensile strength was investigated. The paper was produced from pulp containing 40% pine fibers and 60% eucalyptus bleached kraft fibers, heated to 25 °C, 40 °C, and 50 °C, after which the paper was dried with hot air in the temperature range of 190 to 330 °C. The aim of the research was to determine the influence of the temperature of the paper pulp and drying of the paper formed from it on the degree of PAE bonding with fibers and its self-crosslinking ability. The sheets obtained were tested for wet strength in both the machine direction (MD) and cross direction (CD). The results indicated that the paper drying temperature had a key influence on the increase in its wet strength, while heating the pulp before forming the sheets had a relatively minor effect. The increase in drying temperature to 330 °C allowed the wet tensile index (WTI) to be improved over 100% compared to drying at ambient temperature, with the highest strength demonstrated by samples formed from pulp heated to 50 °C and dried at 330 °C. Paper samples with PAE, tested wet for CD, showed strength at a level of 36 to 44% of the values obtained for MD. The obtained results contribute to the deepening of knowledge on the mechanism of increase in wet strength of PAE-modified towel papers, depending on the temperature conditions used during their production.

The utilization of natural fibers in polymer composites is increasingly popular due to their sustainability, cost-effectiveness, and favorable mechanical properties. This study introduces the novel use of Aristida hystrix fibers, processed for the first time into nano-sized particles via ball milling, to enhance dispersion and bonding within a polyester matrix. These nanoparticles were incorporated into polyester resin at various weight percentages (0 wt%, 1 wt%, 3 wt%, 5 wt%, 7 wt%, and 9 wt%), and composite laminates were fabricated using solvent casting and compression molding techniques. Mechanical properties were evaluated through tensile, flexural, and impact strength tests following ASTM standards. The composite containing 5 wt% nano fiber exhibited the optimum mechanical performance, with tensile strength of 30.13 MPa, flexural strength of 43.685 MPa, and impact strength of 1.87 kJ/m². At higher fiber loadings, particle agglomeration led to performance reduction. Water absorption studies indicated that increased nano fiber content resulted in higher moisture uptake, influencing long-term durability. Scanning Electron Microscopy (SEM) provided insights into fiber–matrix interfacial behavior, dispersion quality, and fracture mechanisms. Overall, this work establishes the first-time development of polyester composites reinforced with nano Aristida hystrix fibers, demonstrating their potential as a sustainable and high-performance material for lightweight structural applications in automotive, aerospace, and marine sectors.