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.

In today’s fast-moving, disrupted business environment, supply chain risk management is crucial. More critically, Industry 4.0 has conferred competitive advantages on supply chains through the integration of digital technologies into manufacturing and logistics, but it also implies several challenges and opportunities regarding the management of these risks. This paper looks at some ways emerging technologies, especially Artificial Intelligence (AI), help address pressing concerns about the management of risk and sustainability in logistics and supply chains. The study, using a systemic literature review (SLR) backed by a mapping study based on the Scopus database, reveals the main themes and gaps of prior studies. The findings indicate that AI can substantially enhance resilience through early risk identification, optimizing operations, enriching decision-making, and ensuring transparency throughout the value chain. The key message from the study is to bring out what technology contributes to rendering supply chains resilient against today’s uncertainties.

This article delves into the controversial practice of utilizing a student’s first language (L1) as a teaching resource in second language (L2) learning environments. Initially, strategies such as code-switching/code-mixing and translanguaging were considered signs of poor linguistic ability. There was a strong push towards using only the target language in foreign language education, aiming to limit the first language’s interference and foster a deeper immersion in the new language. However, later research has shown the benefits of incorporating the first language in bilingual education and language learning processes. It’s argued that a student’s knowledge in their native language can actually support their comprehension of a second language, suggesting that transferring certain linguistic or conceptual knowledge from L1 to L2 can be advantageous. This perspective encourages the strategic use of this knowledge transfer in teaching methods. Moreover, the text points to positive results from various studies on the positive impact of L1 usage in L2 classrooms. These insights pave the way for further exploration into the application of the first language in adult English as a Second Language (ESL)/English as a Foreign Language (EFL) education, particularly regarding providing corrective feedback.

Due to the bounded rationality of decision-makers and the substitution effect of non-green products, retailers are not always profitable when selling green products. To assist retailers who may be disadvantaged in the game, this study constructs a two-stage green supply chain game model, considering the bounded rationality of decision-makers and the substitution effect of non-green products, and analyzes the impacts of two operational strategies that retailers can adopt—price-cutting strategy and early replenishment strategy. The research reveals that retailers tend to lower prices in the second stage when price reductions stimulate consumer purchases, enhancing their profitability. However, strategic retailers may raise prices in the first stage to create room for discounts later, potentially harming consumer interests. Contrary to expectations, anticipating future demand does not always improve supply chain profitability in the early replenishment strategy, which mainly depends on the market environment. Early replenishment deprives retailers of negotiation leverage in the second stage, and bulk orders may lead manufacturers to over-invest in green innovation. Therefore, this strategy is effective only when green innovation costs are low, consumer environmental awareness is high, or price sensitivity is low.

This systematic literature review (SLR) delves into the realm of Artificial Intelligence (AI)-powered virtual influencers (VIs) in social media, examining trust factors, engagement strategies, VI efficacy compared to human influencers, ethical considerations, and future trends. Analyzing 60 academic articles from 2012 to 2024, drawn from reputable databases, the study applies specific inclusion and exclusion criteria. Both automated and manual searches ensure a comprehensive review. Findings reveal a surge in VI research post-2012, primarily in journals, with quantitative methods prevailing. Geographically, research focuses on Europe, Asia Pacific, and North America, indicating gaps in representation from other regions. Key themes highlight trust and engagement’s critical role in VI marketing, navigating the balance between consistency and authenticity. Challenges persist regarding artificiality and accountability, managed through brand alignment and transparent communication. VIs offers advantages, including control and cost efficiencies, yet grapple with authenticity issues, addressed through human-like features. Ethically, VI emergence demands stringent guidelines and industry cooperation to safeguard consumer well-being. Looking ahead, VIs promises transformative storytelling, necessitating vigilance in ethical considerations. This study advocates for continued scholarly inquiry and industry reflection to navigate VI marketing evolution responsibly, shaping the future influencer marketing landscape.