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In linguistics and natural language processing, measuring text features is crucial for representing and revealing the properties of texts in terms of topics, genres, sentiment and more. Current methods predominantly rely on the frequency of linguistic units and rarely consider the syntagmatic properties of these units, which can reflect deeper linguistic characteristics (e.g. syntax and pragmatics). This paper proposes a general method for calculating the sequence complexity of text. By combining the features of word length and word frequency, two specific implementations of this method are provided. Using these two formulas, word sequence complexity of text based on the Brown Corpus and the Gutenberg Corpus is calculated. The results show that word sequence complexity of text indicates a characteristic of gradual stabilization. By comparing random texts with natural texts, it is found that word sequence complexity is influenced by syntactic rules rather than sentence order, and natural texts tend to alternate between words of varying lengths and frequencies. Classification experiment results indicate that the proposed word sequence complexity outperforms commonly used quantitative indicators for representing the genre of text, such as TTR, information entropy, Zipf's law parameters and motifs. [ABSTRACT FROM AUTHOR]

The evolution of the spatiotemporal relationship between urban economic growth and health resources within the Yangtze River Delta urban agglomeration provides an important context for understanding the regional development dynamics in China. Previous studies focused on equity in health-resource allocation and service efficiency, often overlooking the allometric growth relationships between health resources and economic variables. This study employs an allometric growth model to elucidate the changing interactions between the number of medical beds, doctors, and urban economic indicators in the Yangtze River Delta region from 2009 to 2022. Employing Zipf's law and allometric growth modeling, this study analyzed growth trends and revealed significant differences in resource allocation and size changes over time. The main findings suggest that, although resource centralization is a general trend, differences persist, especially in less economically developed regions. This study innovatively introduces an allometric growth model that offers a new perspective on understanding the mechanisms of regional health-resource growth and underscores the significant influence of economic factors on health-resource allocation. This study significantly contributes to the sustainability of urban health systems and provides theoretical support for policy formulations aimed at optimizing the allocation of health resources and strengthening regional economic strategies in the Yangtze River Delta region. [ABSTRACT FROM AUTHOR]

The article explores the quantitative syntactic features of Chinese and English through a comparative study based on dependency relations. It delves into the universality and individuality of languages, emphasizing the dynamic, variable, and ambiguous nature of language. The study employs data-driven research methods, focusing on dependency grammar and valency theory to uncover valuable insights for future research. By utilizing quantitative linguistics, the research aims to define and measure linguistic attributes and units, highlighting the significance of interdisciplinary approaches in language study. [Extracted from the article]

The article "The Impact of Events and Order of Entry" by Nicholas Guthrie explores the concepts of events and launch order in pharmaceutical pipeline forecasting. It discusses how market trends can be influenced by future events and the importance of the order in which brands enter the market. Using real data, the article illustrates how events like product launches and warnings can impact prescription volumes and market shares. The study also delves into Zipf's Law, which suggests that the first product to launch in a market class may have a higher market share. [Extracted from the article]

The document is a note from the editor of Foresight: The International Journal of Applied Forecasting, providing information on the upcoming Foresight Practitioner Conference in Charlotte, North Carolina, and previewing the special feature on Strategic Forecasting in Biopharma in Issue 76. It also announces staffing changes within the Foresight Advisory Board and editorial staff, including departures and new appointments. The editor, Mike Gilliland, shares updates on contributors and editorial changes, highlighting the contributions of departing members and welcoming new additions to the team. [Extracted from the article]

Dependency distance (DD) traditionally refers to the linear distance between two related words in the dependency structure of a sentence (i.e., syntactic-DD). Based on this concept, previous studies have found that language follows a universal rule of DD minimization (DDM), which states that short DDs occur more frequently than long DDs. But if the DDM as a structural rule is universal, does it extend to other levels of language structure? If so, are there any individualities at different levels? This paper proposes the concept of discourse-DD, i.e., the linear distance between two related clauses in a text, to investigate whether the DDM exists at the discourse level. We present a statistical study of discourse-DD using a discourse dependency corpus and compare the statistical results with the syntactic structure. The results show that discourse structure does indeed show the DDM tendency, and even more strongly than syntactic structure. The reasons for this may be that discourse patterns are more flexible than syntactic patterns and clause functions are more dynamic than word functions, and in this case, a stronger DDM is required for discourse comprehension. This paper also explores how linguistic factors such as discourse length, complex sentences, and connectives influence discourse-DDM. The paper deepens the research on DDM of language. • Extending dependency distance minimization study from syntax to discourse to develop a more general language rule. • Proposing the concept of discourse dependency distance and investigate it statistically using a discourse dependency corpus. • Claiming a more stronger dependency distance minimization tendency of discourse than syntax based on statistical comparison. • Giving reasons for stronger dependency distance minimization of discourse from grammatical and cognitive aspects. • Investigating how linguistic factors influence discourse dependency distance minimization. [ABSTRACT FROM AUTHOR]