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.

Online transportation is a new type of service equipped with an internet network, and its presence in Indonesia is considered a service that disrupts the transportation sector. The government is faced with a complex policy problem to regulate online transportation. This article aims to reveal the role of policy actors in the media regarding policy issues and online transportation policy solutions. This article used qualitative analysis and the NPF policy narrative framework approach. This study found that licensing issues and Permenhub were problems that the DIY and Riau governments shared. More specific problems in Riau Province are related to violence issues, and that in DIY are related to congestion problems. The policy solution recommended by policy actors to the media is to make regional level regulations that technically regulate online transportation according to the area conditions.

The experiments were carried out to validate an analytical method and to examine the impact of various decontaminating solutions on the removal of acephate residues from okra. Acephate analysis was performed using HPLC-UV, and sample extraction was done using the QuEChERS method. Method validation encompassed assessing specificity, linearity, precision, accuracy, as well as limits of detection (LOD) and quantification (LOQ). The method exhibited excellent linearity with R² values ≥ 0.99. LOD and LOQ were determined at 0.5 µg mL⁻¹ and 2 µg mL⁻¹, respectively. The results indicated average recoveries ranging from 80.2% to 83.3% with a % RSD below 5%. The decontamination procedures include rinsing with running tap water, soaking in lukewarm water, 2% CH₃COOH, 1% NaCl, 5% NaHCO₃, 0.01% KMnO₄, and in commercially available decontamination products such as nimwash, veggie clean, and arka herbiwash for a duration 10 minutes. Among all the treatments, soaking in nimwash solution showed remarkable effectiveness (96.75% removal), followed by veggie clean (94.97% removal) and arka herbiwash (95.80% removal). Washing okra samples in running tap water was found to be the least effective compared to other treatments.

This research conducts a comparative urban analysis of two coastal cities with analogous tourism models situated in distinct geographical regions: Balneário Camboriú in Brazil and Benidorm in Spain. The study delves into two critical urban phenomena impacting the sustainability of tourist cities, utilising social network data to gather insights into economic and urban activities (Google Places) and spatio-temporal patterns of citizen presence (Twitter). The spatial analysis explores the municipal and, to a more detailed extent, the coastal strip extending 500 m inland from the coastline, spanning the entire length of each city to their municipal boundaries. The analysis uncovers both similarities and differences between the two destinations, offering insights that could inform future development strategies aimed at fostering sustainable urban environments in these well-established coastal tourist areas.

Objective: This research analyzed the psychometric properties of the Ambivalent Classism Inventory (ICA) in Peru. Methodology: A critical review of literature related to poverty, inequality, and structural gaps was conducted, involving 882 participants aged 14 to 89 years (M = 24.61, SD = 9.07). Results: Exploratory-confirmatory factor analyses were satisfactory, finding a similar factorial structure to the original scale and the adaptation (hostile classism, protective paternalism, and complementary class differentiation). Regarding items, there was a reduction, leaving only 12; however, comparing alternative models, the three-factor structure with 12 reagents showed adequate fit (χ² = 214.588, df = 51, p < 0.001; CFI = 0.996; RMSEA = 0.060; SRMR = 0.033), allowing for invariance testing. Practical Implications: The scale allows for investigating attitude profiles of individuals with privileged social class. Contribution: The instrument is a valuable contribution, considering that the nation has a high poverty rate, leading to economic, political, and social inequality among the population.