Volume 19 Issue 3

In recent years, the custom wardrobe market has been steadily developing. While meeting the functional needs of users, it is gradually shifting towards aesthetic preferences. Rapidly grasping users’ preferences for the appearance of custom wardrobes is a key focus of current research. This study collected a large number of decorative surface images of custom wardrobes and objectively analyzed the design features based on color moments and Tamura texture feature data in computer image analysis methods. K-means cluster analysis was performed on the feature data. Collected images of the points closest to the cluster centers were further screened to select representative finish images, and finally a questionnaire survey was conducted at Nanjing Forestry University, with the help of semantic differential method and factor analysis. The characteristics of the samples were comprehensively summarized to infer design elements. The study found that warm-toned, medium-low saturation, and medium brightness surfaces were preferred by the panel. Different colors, contrasts, saturations, brightness, element features, and arrangements have significantly different effects on visual perception. These conclusions can provide a reference for subsequent custom wardrobe design.

Carbon quantum dots (CQDs) are an emerging type of multifunctional nanomaterial. They have unique optical and electronic properties based on their quantum size effect and limiting effect. The carbon quantum dot prepared from biomass is green and environmentally friendly, and it can also achieve a high comprehensive utilization of undervalued biomass wastes. Biomass carbon quantum dots with abundant surface functional groups and good biocompatibility show great potential in ion detection and bioimaging. This review paper focuses on the synthesis methods of CQDs from biomass and the perspective of their applications in recent years, as well as the challenges in the future.

Bark, the outermost tissue, plays an important role in protecting trees from damage induced by living organisms and the surrounding environment. Bark differs from the xylem primarily by the presence of suberin in cork cell walls. However, few studies have examined the role of suberin and its interactions with other chemical components in the cork. Consequently, this study aimed to understand the distribution of chemical components, including suberin and lignin, and their respective roles in cork cell walls, using Cerasus jamasakura (Siebold ex Koidz.) H. Ohba. Suberin and lignin were gradually and selectively removed from thin strip specimens. Fourier transform infrared (FTIR) spectroscopy suggested that desuberinization removed both suberin and part of the other matrix substances within a few minutes of treatment, whereas delignification exclusively removed lignin. Further microscopic observation revealed that suberin present was mainly in the secondary wall of cork cells, whereas lignin was present in both the tertiary wall and compound middle lamella. In addition, the cell wall collapse of the cork was only found in desuberinized specimens, whereas delignified specimens only showed monotonic contraction. Taken together, these results suggest that the presence of suberin in the cork contributes to the shape stability of cork cell walls.

It is difficult to predict index values or stock prices with a single financial formula. They are affected by many factors, such as political conditions, global economy, unexpected events, market anomalies, and the characteristics of the relevant companies, and many computer science techniques are being used to make more accurate predictions about them. This study aimed to predict the values of the XKAGT index by using the monthly closing values of the Borsa Istanbul (BIST) Forestry, Paper and Printing (XKAGT) index between 2002 and 2023, and the machine learning techniques artificial neural networks (ANN), random forest (RF), k-nearest neighbor (KNN), and gradient boosting machine (GBM). Furthermore, the performances of four machine learning techniques were compared. Factors affecting stock prices are generally classified as macroeconomic and microeconomic factors. As a result of examining the studies on determining the macroeconomic factors affecting the stock markets, 10 macroeconomic factors were determined as input. The macroeconomic variables used were crude oil price, exchange rate of USD/TRY, dollar index, BIST100 index, gold price, money supply (M2), S&P 500 index, US 10-year bond interest, export-import coverage rate in the forest products sector, and deposits interest rate. It was determined that all machine learning techniques used in the study performed successfully in predicting the index value, but the k-nearest neighbor algorithm showed the best performance with R²=0.996, RMSE=71.36, and a MAE of 40.8. Therefore, in line with the current variables, investors can make analyzes using any of the ANN, RF, KNN, and GBM techniques to predict the future index value, which will lead them to accurate results.

Giant snowdrop (Galanthus elwesii Hook. f.) is reported on CITES lists as the most important wild-collected export flower bulb of Turkey. After the destruction caused by extensive collecting for many years, collection and trade have been controlled by the government since the late 1980’s. Export quotas are annually set by a technical committee, following field inspections by scientific teams. Small bulbs (under-sized) are also unintentionally collected from nature together with marketable sized bulbs (> 4 cm). Low success rate at cultivation of field grown snowdrop and loss of these small bulbs reveals the necessity of the studies on soilless culture. This study aimed to select the suitable growing media and mineral nutrition for snowdrop bulb production. Under-sized (unmarketable) bulbs of Galanthus elwesii Hook. f. were cultivated in four different growing media (perlite, coco-peat, soil, or spent mushroom compost + perlite) with four different nutrient solutions. The growing media affected most of the investigated parameters (sprouting time, sprouting ratio, total weight and increase ratio, number of harvested bulbs, and bulb grades). No significant effect of nutrient solutions was determined on the parameters. Spent mushroom compost + perlite appeared to be the most effective growing media.

In the 21^st century, with active policy support, the smart hardware industry ushered in rapid development of the Internet of things, big data, and other emerging technologies, which has brought people a more intelligent way of life. Smart product retail experience stores have also emerged as a result. One of the key aspects of the consumer shopping experience is highlighted by the furniture design of the smart display table. This study considers the background of consumer rejuvenation and the diversification of needs, through in-depth examination of user pain points, and output of the design of smart product display table from the user experience perspective. Analytic Hierarchy Process (AHP) and Function Analysis System Technique (FAST) are used to systematically refine the smart display table requirements, synthesize the weights of the sorting factors, quantify the demand contribution value, and transform the requirements into functional design points. The goal is to enhance the user experience, while achieving exterior styling and usage features of the smart display table. This study provides theoretical and practical support for furniture design in the smart hardware industry, emphasizing the role of consumer experience and needs in product design and providing considerations for design research.

Angelica sinensis polysaccharides are important active ingredients and  biological resources in traditional Chinese medicine. Properly changing the fermentation conditions of microorganisms may alter the yield of fermentation products. Based on single factor test results, three factors with great influence on the yield of Angelica sinensis polysaccharides produced by Aspergillus niger were optimized: initial pH value, fermentation time, and culture temperature. According to the box Behnken central combination principle, a response surface analysis scheme with three factors and three levels was designed, and the yields of active polysaccharide of Angelica sinensis were taken as the response value to optimize the fermentation process. The results of response surface analysis showed that under the optimized fermentation temperature of 30 °C, cultivation time of 8 days, and initial pH value of 5, the predicted yield of active polysaccharides from Angelica sinensis was 15.5%, while the actual value was 15.35%, which was 0.11% lower than the predicted value. This indicated that using response surface analysis to optimize the fermentation conditions of Angelica sinensis polysaccharides was reasonable and feasible. This method can effectively improve the biological resource utilization rate of Angelica sinensis polysaccharides.

The flexural performance of a glulam wood/PVC composite (GWPVC) hollow member, which was assembled from four elements with WPVC composite hollow sections to create a double I-section, was studied using two methods: the analytical method with iteration technique (AMIT) and the finite element method (FEM). Experiments verified the predictions from AMIT and simulations from FEM to determine the most suitable method for the parametric studies. This investigation explored the variations in slenderness ratio and the flange and web thickness to enhance and study their impact on flexural performance. In parametric studies, equal cross-sectional areas were used to facilitate comparisons and maintain production costs. The importance of bond strength at the contact surfaces in assembling a GWPVC hollow member led to bonding tests and confirmed sufficient strength at contact surfaces. In four-point bending tests, the GWPVC hollow member exhibited a brittle mode with flexural tensile failure without delamination. The initial MOE, MOR, and maximum deflection values were 5,140 MPa, 29.8 MPa, and 47.8 mm, respectively. The parametric study employs AMIT to investigate flexural performance and reveals that varying the slenderness ratio affected the initial stiffness, maximum deflection, and ultimate load. Flexural performance can be improved by making minor adjustments.

The energy needed for the dewatering and drying of wet paper web represents around half of the energy consumption of papermaking processes. The present work examined whether the dewatering and drying of paper could be enhanced during a previous pulp drying process by pretreating the fibers with polyamide-epichlorohydrin (PAE). According to the hypothesis, the cured PAE restrains swelling and water absorption of water-wetted fibers by forming a fiber-bound, self-crosslinked polymer-network on the fiber surfaces. The hypothesis was tested by adding PAE to never-dried kraft pulp slurry followed by pulp thickening, drying, and final curing of the PAE-resin. After this, the PAE-treated fibers were dispersed in water, and their water retention values (WRV) and Shopper-Riegler values (^○SR) were measured. The PAE pretreatments notably decreased the fibers´ WRV and ^○SR, indicating improved water removal of paper web in the paper machine forming and drying section. Compared to chemical crosslinking pretreatments, which also can be used to decrease fibers WRV and ^○SR-value, a notable advantage of PAE-pretreatment is milder required curing conditions of the PAE, which makes implementation of the method easier in practice. Due to decreased fiber-to-fiber bonding capability, the PAE-treated specialty fibers could take advantage especially as a bulking aid of paperboard, tissue, and absorbent materials.

Ultraviolet (UV) radiation causes skin damage including oxidative stress, inflammation, and photoaging. Extremophile fermentation products have been found to effectively protect the skin from UV-induced damage. This study aimed to investigate the impact of acid-induced stress on the content of bioactive compounds, as well as the anti-inflammatory and anti-photoaging properties of sorghum fermentation by the extremophilic Monascus pilosus. The study compared acid-stress fermentation (ASF) of sorghum with conventional fermentation (CF) and examined differences in total phenolic content, antioxidant activity, and short-chain fatty acid levels. Using gas chromatography–mass spectrometry assay, the ASF sample had lower total phenolic content compared to CF, but significantly higher levels of short-chain fatty acids. Butyric acid was the predominant metabolite in the ASF sample, followed by propionic acid. The ASF sample exhibited superior protection for UV-irradiated human keratinocytes by inhibiting apoptosis, reducing ROS, and downregulating inflammatory mediators. It also decreased metalloproteinases expression levels, increased collagen and elastin production, and mitigated UV-induced photoaging. The effects of ASF samples were evaluated in volunteers, and the results confirmed the ASF sample’s effectiveness in ameliorating UV-induced skin symptoms, including pigmentation, redness, and wrinkles. These findings conclude that acid-stress enhances the anti-inflammatory and anti-photoaging capabilities of Monascus pilosus fermented sorghum.