The study focused on investigating the effects of varying levels of HA (HA₁ = 0, HA₂ = 25, HA₃ = 50, HA₄ = 75, and HA₅ = 100) on Red Dragon, Red Prince, and Red Meat varieties of red radish. This analysis aimed to unravel the relationship between different levels of HA and their impact on the growth and productivity of red radish genotypes. The findings revealed that the Red Prince genotype attained the utmost plant height of 24.00 cm, an average of 7.50 leaves per plant, a leaf area of 23.11 cm², a canopy cover of 26.76%, a leaf chlorophyll content of 54.60%, a leaf fresh weight of 41.16 g, a leaf dry weight of 8.20 g, a root length measuring 9.73 cm, a root diameter of 3.19 mm, a root fresh weight of 27.60 g, a root dry weight of 6.75 g, and a remarkable total yield of 17.93 tons per hectare. The implications of this study are poised to benefit farmers within the Dera Ismail Khan Region, specifically in the plain areas of Pakistan, by promoting the cultivation of the Red Prince variety.

Nanotechnology is a subject that studies, processes, and applies various functional materials, equipment, and systems, and controls substances on a nanoscale. Nanomedicine refers to its application in diagnosing, treating, preventing, and monitoring various diseases. Drugs administered through eye drops must travel a long distance to avoid various eye barriers reaching the posterior segment of the eye, to achieve the lowest drug level. This review focuses on nanotechnology-based eye disease treatment systems and highlights the obstacles affecting the drug management of eyes and nano-systems for the treatment of eye diseases. This paper summarizes the development prospect of nanotechnology and the challenges it faces in the treatment and diagnosis of ophthalmic diseases, to provide information and new ideas for the implementation of treatment and the development of a refractory eye disease management system.

Every plant is significantly important in tackling climate change, including Makila (Litsea angulata BI) an endemic wood species found in the forest of Moluccas Provinces. Therefore, this research aimed to examine the role of the Makila plant in tackling climate change by measuring biomass content using constructing an allometric equation. The method used was a destructive sampling, where 40 units of Makila plant at the sampling level were felled, and sorted according to root, stem, branch, rating, and leaf segments. Each segment was weighed both at wet and after drying, followed by a classical assumption test in data processing, and the formulation of an allometric equation. The regression model was examined for normality and suitability in predicting independent variables, ensuring there were no issues with multicollinearity, heteroscedasticity, and autocorrelation. The results yielded a multiple linear regression, namely: Y = −1131.146 + 684.799X₁ + 4.276X₂, where Y is biomass, X₁ is the diameter, and X₂ is the tree height. Based on the results of the t-test: variable X₁ partially affected Y while variable X₂ partially had no effect on Y. The F-test indicated that variables X₁ and X₂ jointly affected Y with R Square: 0.919 or 91.9% and the rest was influenced by other unexplored factors. To simplify biomass prediction and field measurement, a regression equation that used only 1 independent variable, namely tree diameter, was used for the experiment. Allometric equation only used 1 variable, Y = −1,084,626 + 675,090X₁, where X₁ = tree diameter, Y = Total biomass with R = 0.957, and R² = 0.915. Considering the potential for time, cost, and energy savings, as well as ease of measurement in the field, the biomass of young Makila trees was simply predicted by measuring the tree diameter and avoiding the height. This method used the strong relationship between biomass, plant diameter, and height to facilitate the estimation of biomass content accurately by entering the results of field measurements.

Dong brocade, a fabric renowned for its intricate patterns and ethnic symbolism, has been woven by the Dong people for generations, showcasing their cultural significance. Traditional plant dyeing technology is one of the main aspects of Dong brocade but the documentation and understanding of this is still rather limited. With regard to the use of plant dye in Dong brocade, it is not as well explored as it should be since it has a traditional aspect. The main purpose is to investigate and apply the traditional plant dyeing technique to Dong brocade for the improvement of that sustainable concept and the preservation of cultural assets. Therefore, 121 Dong villagers were interviewed to elicit their awareness regarding prehistoric plant dyeing. By observing the dyeing conditions, this study provided accurate perception and learned how to differentiate between natural and synthetic mordants through ethnobotanical perception. The strategy is intended to integrate sustainable products into Dong brocade, employing orthogonal array development to find the right dyeing conditions for corresponding plant dyes. Research revealed that 8 genera of plants which include 7 species are used in dyeing Dong brocade. The findings presented in this work prove the effectiveness of the use of plant dyes in Dong brocade, showing its advantages with 30% of frequency and CI (Color Index) indices, 8% of them being cultural. 5 for ethnic cultural sustainment, developmental and bio-diversity reasons respectively. The unique integration between the traditional dyeing technique in Dong brocade and the utilization of sustainable resources is very promising for the improvement of identity enhancement and embodiment, and the preservation of the environment.

Indonesia’s stock market has seen an increase in investment due to the ease of investing and the availability of information about stocks on different social media platforms. This research uses a social network approach to analyze overconfidence behavior in millennial stock investors. This research uses a descriptive quantitative method. The population used in this study are capital market investors in the Greater Solo area who are millennials (<30 years). The number of stock investors in the Greater Solo area is 60,542 investors. The sampling technique in this study was non-probability sampling using purposive sampling. This research uses the AMOS SEM (Structural Equation Model) analysis tool. The conclusion of this study is that millennial investors’ overconfidence behavior increases influenced by financial literacy. investor skills. family ties and friendship ties. The contribution of this research can be applied to understand and educate millennial investors in order to overcome overconfidence behavior so that they can anticipate the losses received. This research may have implications for improving Behavioral Finance Integration Incorporating insights from behavioral finance into investment strategies can help mitigate the negative effects of overconfidence. The limitation in this study is that the scope used in the study is only in the greater solo area.