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We present an application of the fractal "chaos game representation" method in climatology for characterizing temporal precipitation aggregation patterns. To this aim, we establish an analogy with linguistic analysis considering precipitation as a discrete variable (e.g. rain, no rain). Each weekly, or monthly, symbolic sequence of observed precipitation is then considered a "word" and the climatological time series observed at a particular gauge defines a "language." The distribution of different words within the language characterizes the particular precipitation aggregation scheme. In this paper we show that the chaos game representation method provides a graphical representation (a fractal pattern, or fingerprint) of the distribution of words and also gives a quantitative characterization in terms of parameters such as the box-counting dimension and the entropy. We show that different climates exhibit characteristic patterns with different fractal exponents and entropies. As an illustrative application, the method is used for automatic regionalization of a set of gauges in the Iberian peninsula, showing that these new indices outperform standard averaged statistics (monthly means, etc.).

This chapter explores the implications of the US–China policy conflict on the global semiconductor value chain. The ongoing policy conflict between the US and China is causing significant disruptions in the global semiconductor industry. Firms are forced to navigate these adverse conditions, with outcomes varying greatly depending on their geographical location, strategic decisions and specific role within the global value chain. This chapter investigates this complex scenario, utilizing qualitative data, guided by established business theory models. The analysis delves into the conflict’s implications for multinational enterprises’ decision-making, competitive factors for China and the US, industry governance and industry upgrading. The results suggest a challenging near-term outlook for Chinese firms contrasted with potential growth for non-Chinese foundries. This situation is predicted to evolve, with China possibly surfacing as a significant competitor and a trend toward regionalization in the long run. In the short term, the industry could face disruption in innovation and collaboration. However, the pressures could also stimulate competitiveness and encourage supply chain diversification in the long term. This investigation, while insightful, recognizes its limitations. Its focus is narrowed to a few case studies and leans heavily on qualitative data. Moreover, the volatile nature of the industry and geopolitical landscape can impact the longevity of the findings. Future research could further elaborate on the long-term implications and potential strategies to counter the emerging challenges.

Municipal solid waste management (MSWM) is an important, practical and challenging environmental subject. Regionalization of MSWM program is more complicated due to the involvement of multi-municipality and multi-facility issues. Therefore, an effective technique capable of solving regional MSWM problems is necessary for decision makers. This paper employed linear programming techniques to establish a optimization model which is able to achieve regional MSWM strategies with the minimum costs. The results of investigating a real world case study in central Taiwan indicate that regionalization of MSWM program is more economical and efficient.

Accurate climate data is an essential environmental factor to quantify ecology, geography and other related research fields. In this paper, we performed thin-plate smoothing spline interpolation implemented in ANUSPLIN on monthly climate data and obtained precipitation and temperature monthly interpolation surfaces in Kangdian area. Error analysis showed the RTMSE of temperature was less than 0.513 and the RTMSE of precipitation was less than 12.700 in most months. Compared with IDW and Kriging method, the proposed method could get more accurate results. It indicated that ANUSPLIN method could be the optimal spatial interpolation method in interpolating the monthly meteorological data in Kangdian area and other areas with complex terrain.