This study’s primary objective is to determine the financial repercussions, including expenses, profits, and losses, that certain stakeholders in the Tuong-mango value chain face at various distribution stages. This was achieved through the utilisation of stakeholders cost-benefit value chain analysis. These individuals collectively contributed 849 sample observations to the dataset including 732 farmers, 10 cooperative, 32 collectors, 25 wholesalers, 30 retailers, 12 exporters and processors, and 08 grocery stores/fruit. The robust financial performance of the Tuong-mango value chain is attributable to its integrated economic efficiency, as evidenced by its over USD 1 billion in revenue and USD 98.2 million in net income. The marketing channels, specifically channels 1, 2, and 3, generate a total of USD 906.1 million in revenue, yielding a net profit of USD 81.9 million. The combined sales from domestic marketing channels 4 and 5 total USD 160 million, yielding a net profit of USD 16.2 million. The findings indicate that due to their limited scope and suboptimal grade 1, farmers are the most vulnerable link in the supply chain. This study proposes three strategies for augmenting quality, fostering technological advancement, and facilitating the spread of benefits. This study’s findings contribute to the existing literature on value chain analysis as it pertains to various tropical fruits and vegetables. The study provides empirical evidence supporting the utility of the value chain method in policy formulation.

The livelihood of ethnic minority households in Vietnam is mainly in the fields of agriculture and forestry. The percentage of ethnic minorities who have jobs in industry, construction, and services is still limited. Moreover, due to harsh climate conditions, limited resources, poor market access, low education level, lack of investment capital for production, and inadequate policies, job opportunities in the off-farm and non-farm activities are very limited among ethnic minority areas. This paper assessed the contribution of livelihood diversification activities to poverty reduction of ethnic minority households in Son La Province of Vietnam. The analysis was based on the data using three stages sampling procedure of 240 ethnic minority households in Son La Province. The finding showed that the livelihood diversification activities had positively significant contribution to poverty reduction of ethnic minority households in Son La Province. In addition, the factors positively affecting the livelihood choices of ethnic minority households in Son La Province of Vietnam are education level, labor size, access to credit, membership of associations, support policies, vocational training, and district. Thus, improving ethnic minority householder’s knowledge through formal educational and training, expanding availability of accessible infrastructure, and enhancing participation of social/political associations were recommended as possible policy interventions to diversify livelihood activities so as to mitigate the level of poverty in the study area.

The business life cycle is examined through a comprehensive literature review in this academic study. Our initial approach involves searching for relevant articles on firm life cycle and strategy using the Web of Science and Scopus databases. We conduct bibliometric analyses to identify key contributors and recurring keywords. Subsequently, we select twenty-seven research papers to explore the Theory Development, Characteristics, Context, and Methodology (TCCM) framework for firm life cycle and strategy. Our analysis summarizes corresponding business strategies for each stage, including the use of Initial Management Control Systems (MCS) in the introduction phase. As companies grow, a high inventory-to-sales ratio may hinder effectiveness, but it proves beneficial in the growth and revival stages. Mature companies excel in green process innovation and engage more in Corporate Social Responsibility (CSR) activities. In the decline stage, firms use cost efficiencies, asset retrenchment, and core activity focus for recovery, signaling commitment to a successful turnaround. However, there is a research gap in exploring appropriate global strategies for various life cycle stages, providing an opportunity for additional articles to thoroughly investigate this relationship and assess multinational enterprises’ success trajectories throughout their life cycles.

Magnetite magnetic nanoparticles (MNP) exhibit superparamagnetic behavior, which gives them important properties such as low coercive field, easy superficial modification and acceptable magnetization levels. This makes them useful in separation techniques. However, few studies have experimented with the interactions of MNP with magnetic fields. Therefore, the aim of this research was to study the influence of an oscillating magnetic field (OMF) on polymeric monolithic columns with vinylated magnetic nanoparticles (VMNP) for capillary liquid chromatography (cLC). For this purpose, MNP were synthesized by coprecipitation of iron salts. The preparation of polymeric monolithic columns was performed by copolymerization and aggregation of VMNP. Taking advantage of the magnetic properties of MNP, the influence of parameters such as resonance frequency, intensity and exposure time of a OMF applied to the synthesized columns was studied. As a result, a better separation of a sample according to the measured parameters was obtained, so that a column resolution (R_s) of 1.35 was achieved. The morphological properties of the columns were evaluated by scanning electron microscopy (SEM). The results of the chromatographic properties revealed that the best separation of the alkylbenzenes sample occurs under conditions of 5.5 kHz and 10 min of exposure in the OMF. This study constitutes a first application in chromatographic separation techniques for future research in nanotechnology.

To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.

The flipped classroom (FC) model has long brought significant benefits to higher education, secondary, and elementary education, particularly in improving the quality and effectiveness of learning. However, the implementation of FC model to support elementary students in developing self-learning skills (autonomous learning, independent study, self-directed learning) through technology still faces numerous challenges in Vietnam due to various influencing factors. Data for the study were collected through direct questionnaires and online surveys from 517 teachers at elementary schools in Da Nang, Vietnam. Based on SEM analysis, the study identified factors such as perceived usefulness, accessibility, desire, teaching style, and facilitating conditions. The research findings indicate that factors like the perceived effectiveness of the model, teaching style, and facilitating conditions have a positive correlation with the decision to adopt the FC model. Therefore, to encourage the use of the FC model in teaching, it is essential to raise awareness of the model’s effectiveness, improve teaching styles, and create favorable conditions for implementation.