Farming areas are an indispensable part of conventional agricultural strategy. They contribute to the production of medicine and economical crops, and their scale is continuously expanding. However, intensive planting strategies can cause hazardous consequences, as the rapid expansion of farming technology and monoculture cultivation model can add a huge pressure to the mass ecosystem. These factors disrupt the local ecological balance and can further weaken the biodiversity in local region. Specifically, the conversion of primary forests into monoculture plantations disrupts multi‑trophic ecological networks, triggers habitat fragmentation and pollinator population collapse, and transforms carbon sinks into carbon emission sources. This article explores the environmental impacts and regulatory challenges caused by the over development of pharmaceutical companies. The study employs literature analysis and case study methods. For the administration part, the analysis indicates the systemic problems, such as the none-transparent supply chain, market leakage, coupled with the fragmentation of national-level definitions of "forests" under the REDD+ framework, collectively gives rise to regulatory arbitrage and undermines law enforcement effectiveness. In the end of the research, the conclusion indicates the regulation of exploitation of modern farming requires the multi-party joint management to ensure the stable development of farming techniques while controlling the side effects to the ecosystem.

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Stock price prediction is a typical but difficult problem in quantitative finance that can help investors make decisions and manage risks. However, due to the high volatility of the financial market and other reasons, it cannot be known in advance. The three main methodological paradigms in the current studies are introduced systematically here. The first is feature selection and extraction to improve the quality of the model's input data from raw data. The second type is a neural network-based approach; RNNs, LSTMs and Transformers are used to learn complex, non-linear temporal dependencies in the historical data. The third kind is a graph-structure-based method that builds a model of the connections among all stocks to study cross-asset spillover effects. The review shows that each method has distinct strengths and is suited to different market conditions, with no single approach dominating all scenarios. A primary insight is that future research should move towards integrating these complementary methodologies and leveraging multi-modal data sources, which holds the potential for developing more robust and economically interpretable predictive frameworks.

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This study examines how Sephora's online platform organizes products through its retailer-defined Women and Men categories, and whether this classification is related to listed fragrance prices. The study uses 8,494 product listings to describe the platform's overall taxonomy and then examines 974 Women- and Men-categorized fragrances using nested OLS models with HC3 robust standard errors. The models control bottle size, fragrance concentration, brand, customer rating, and product popularity. The unadjusted comparison shows that Women-categorized fragrances have lower listed prices but are generally sold in smaller bottles. After controlling bottle size, the direction of the association reverses. In the preferred model, Women categorization is associated with approximately 19.3% higher listed prices. The main robustness checks produce estimates of about 12% to 19%. These findings suggest that price patterns depend on product comparability and platform taxonomy, but do not establish discriminatory pricing. Future research should compare multiple retailers, use more balanced, closely matched samples, and track prices and taxonomies over time.

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With the intensification of market competition, consumer psychology and behavior have received attention and importance from enterprises. Relying solely on low prices to shape unique brand advantages, the attached value behind products has become an advantage in market competition. This article is based on a symbolic perspective, exploring how jewelry brands can use brand positioning, IP aesthetics to shape, and personally quantify jewelry. Under the consumption concept of the Z era, the significance of jewelry goes beyond its own value, becoming a carrier of consumers' self-expression of emotional value and a symbol of identity. Taking Chaohongji as an example, this study analyzes the marketing strategy of products based on Chaohongji's brand building as a case, explores the transformation of people's consumption concepts in the new era, the inheritance of intangible cultural heritage, and the practical path of IP character creation. Research has found that aesthetic shaping is not only about product design and aligning stories with consumers, but also about emotional connections between consumers and products. Creating unique product features is the current trend for jewelry brands. This study provides reference for the transformation path of traditional jewelry in the same industry and explores consumer psychology.

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