Maps of forest stand condition—the current phase of the forest-forming process—will be useful for foresters in their forest management in addition to the forest planning and cartographic materials. The mapping methodology was applied in the test area of the Bolshemurtinsky forest district of the Krasnoyarsk region, which is typical for the southern taiga forests of East Siberia. Source data for mapping was obtained on the basis of descriptions of the forest subcompartments on the GIS attribute table of the forest district. Forest stand confinement to the terrain relief indicators was identified on the basis of the SRTM 55-01 digital terrain model data. Spatial analysis has been performed using the ArcGIS Spatial Analyst module. Mapping capability has been shown not only for the year of forest inventory but also for the earlier period of time. To determine the predominant species and the age of the 100-year-old forest stand, a scheme was proposed in which the conceivable options are typified depending on the succession trend, the forest stand age prior to disturbance, and the period of reforestation. Map fragments of the test area as of 2006—the year of forest inventory—and as of 1906—the year of the intensive colonization beginning in southern Siberia—are demonstrated. Maps of forest condition in the test area represent successions that are typical in the southern taiga forests of Siberia: post-harvest, pyrogenic, and biogenic. The methodology of forest condition mapping is universal.

Highly nutritive and antioxidants-enriched okra (Abelmoschus esculentus) gets sub-optimal field yield due to the irregular germination coupled with non-synchronized harvests. Hence, the research aimed at assessing the combined impact of seed priming and field-level gibberellic acid (GA₃) foliar spray on the yield and post-harvest quality of okra. The lab studies were conducted using a complete randomized design (CRD), while the field trials were performed following a factorial randomized complete block design (RCBD) with three replications. Okra seeds were subjected to ten different priming methods to assess their impact on seed germination and seeding vigor. In the premier step, okra seeds were subjected to ten different priming methods, like hydro priming for 6, 12, and 18 h, halo priming with 3% NaCl at 35 ℃, 45 ℃, and 60 ℃, acid priming with 80% H₂SO₄ for 2.5, 5, and 10 min. Based on the observation, hydro priming for 12 h exhibited the best germination rate (90%), followed by halo seed priming at 60 ℃ and acid priming for 5 min. Furthermore, the halo priming at 60 ℃ demonstrated the greatest seedling vigor index (1965), whereas acid priming for 5 min resulted in favorable outcomes in terms of early emergence in 2.66 days. In addition, varying concentrations of GA₃ (0, 100, 200, and 300 ppm) were also administered to the best three primed seedlings for evaluating their field performance. The findings indicated that applying GA₃ at a concentration of 300 ppm to seedlings raised through acid priming (80% H₂SO₄ for 5 min) resulted in improved leaf length, reduced time to flowering (first and 50%) and harvest, increased pod diameter, individual pod weight, and yield per plant (735.16 g). Additionally, the treatment involving GA₃ at 300 ppm with halo priming (3% NaCl) at 60 ℃ exhibited the longest shelf life (21 days) of okra with the lowest levels of rotting (6.73%) and color change (1.12) in the polyethylene storage condition.

This study aimed to measure the impact of implementing mechanisms of accounting data governance, represented by International Accounting Standards, internal auditing, external auditing, audit committees, disclosure and transparency, and performance evaluation, on the quality of financial reporting data for the commercial banks listed on the Amman Stock Exchange, totaling (15) banks. To achieve the objectives of this study, a descriptive-analytical approach was adopted by developing a questionnaire to collect the primary data measuring the study variables. The questionnaire was distributed to employees in the financial and control departments of these banks, with a total of (375) respondents from the total study population of (733) individuals. Appropriate statistical methods were used to analyze the data, test hypotheses, and the results of this study revealed a strong positive impact of five variables of accounting data governance mechanisms on achieving the quality of financial reporting data. These variables are ranked from highest to lowest in terms of the strength of impact and correlation with the quality of financial reports: disclosure and transparency, external auditing, International Accounting Standards, internal auditing, and audit committees. However, there was no impact of the performance evaluation governance variable on achieving the quality of financial reporting data. These results call on the management of commercial banks in the study to commit to the objective implementation of the requirements of accounting data governance mechanisms as stipulated by international professional assemblies.

Outsourcing logistics operations is a common trend as businesses prioritize core activities. Establishing a sustainable partnership between businesses and logistics service providers requires a systematic approach. This study is needed to develop a more effective and adaptive framework for logistics service provider selection by integrating diverse criteria and decision-making methodologies, ultimately enhancing the precision and sustainability of procurement processes. This study advocate for leveraging industry-based knowledge in procurement, emphasizing the need to define decision-making elements. The research analyzes nearly 300 logistics procurement projects, using a neural network-based methodology to propose a model that aids businesses in identifying optimal criteria for evaluating logistics service providers based on extensive industry knowledge. The goal of this study is to develop and test a practical model that would support businesses in choosing most suitable criteria for selection of logistics service providers based on cumulative market patterns. The results of this study are as follows. It introduces novel elements by gathering and systematizing unique market data using developed data processing methodology. It innovatively classifies decision-making elements, allocating them into distinct groups for use as features in a neural network. The study further contributes by developing and training a predictive model based on a prepared dataset, addressing pre-defined goals, expectations related to green logistics, and specific requirements in the tendering process for selecting logistics service providers. Study is concluded by summarizing suggestions for future research in area of adopting neural networks for selection of logistics service providers.

This study aims to discover the relationship between growth sales, capital structure, and corporate governance on financial performance of energy and basic material sector public companies in Indonesia. Financial performance is observed from 2 aspects: market performance (Tobin's Q) and profitability performance (ROA). The population in this study is firms in the energy and basic material sector on Indonesia Stock Exchange. The total population is 248 firms. 39 firms were selected as samples. The data is obtained from the annual report which starts from the period 2018 to 2022. A total of the population was determined as samples by purposive sampling method. Data analysis using panel data regression. The result shows: 1) Growth Sales have a significant influence on market performance; however, it does not have a significant effect on profitability performance. 2) Capital Structure significantly influences market and profitability performance 3) Corporate governance significantly influences market and profitability performance. Suggestions for companies that must strive to increase sales, maintain good corporate governance and pay attention to the company's capital structure in a balanced manner.