Past, present and future mathematical models for buildings (i)

This is the first of two articles presenting a detailed review of the historical evolution of mathematical models applied in the development of building technology, including conventional buildings and intelligent buildings. After presenting the technical differences between conventional and intelligent buildings, this article reviews the existing mathematical models, the abstract levels of these models, and their links to the literature for intelligent buildings. The advantages and limitations of the applied mathematical models are identified and the models are classified in terms of their application range and goal. We then describe how the early mathematical models, mainly physical models applied to conventional buildings, have faced new challenges for the design and management of intelligent buildings and led to the use of models which offer more flexibility to better cope with various uncertainties. In contrast with the early modelling techniques, model approaches adopted in neural networks, expert systems, fuzzy logic and genetic models provide a promising method to accommodate these complications as intelligent buildings now need integrated technologies which involve solving complex, multi-objective and integrated decision problems.

Past, present and future mathematical models for buildings (ii)

This article is the second part of a review of the historical evolution of mathematical models applied in the development of building technology. The first part described the current state of the art and contrasted various models with regard to the applications to conventional buildings and intelligent buildings. It concluded that mathematical techniques adopted in neural networks, expert systems, fuzzy logic and genetic models, that can be used to address model uncertainty, are well suited for modelling intelligent buildings. Despite the progress, the possible future development of intelligent buildings based on the current trends implies some potential limitations of these models. This paper attempts to uncover the fundamental limitations inherent in these models and provides some insights into future modelling directions, with special focus on the techniques of semiotics and chaos. Finally, by demonstrating an example of an intelligent building system with the mathematical models that have been developed for such a system, this review addresses the influences of mathematical models as a potential aid in developing intelligent buildings and perhaps even more advanced buildings for the future.

The climate and environment of Byzantine Anatolia: integrating science, history, and archaeology

The integration of high-resolution archaeological, textual, and environmental data with longer-term, low-resolution data affords greater precision in identifying some of the causal relationships underlying societal change. Regional and microregional case studies about the Byzantine world—in particular, Anatolia, which for several centuries was the heart of that world—reveal many of the difficulties that researchers face when attempting to assess the influence of environmental factors on human society. The Anatolian case challenges a number of assumptions about the impact of climatic factors on socio-political organization and medium-term historical evolution, highlighting the importance of further collaboration between historians, archaeologists, and climate scientists.

Ethnobiology and the evolution of the human mind

An evolutionary perspective on human thought and behaviour indicates that we should expect to find universal systems of perception, classification, and decision-making regarding the natural world. It is the interaction between these evolved aspects of the human mind, the biodiversity of the natural world, and unique historical, social, and economic contexts within which individuals develop and act that gives rise to cultural diversity. The palaeoanthropological record also indicates that language is a recently evolved phenomenon. This suggests that linguistic approaches in ethnobiology are likely to provide only a partial understanding of how humans perceive, classify, and engage with the natural world.

Frequency of word-use predicts rates of lexical evolution throughout Indo-European history

Greek speakers say "ovpa", Germans "schwanz'' and the French "queue'' to describe what English speakers call a 'tail', but all of these languages use a related form of 'two' to describe the number after one. Among more than 100 Indo-European languages and dialects, the words for some meanings (such as 'tail') evolve rapidly, being expressed across languages by dozens of unrelated words, while others evolve much more slowly-such as the number 'two', for which all Indo-European language speakers use the same related word-form(1). No general linguistic mechanism has been advanced to explain this striking variation in rates of lexical replacement among meanings. Here we use four large and divergent language corpora (English(2), Spanish(3), Russian(4) and Greek(5)) and a comparative database of 200 fundamental vocabulary meanings in 87 Indo-European languages(6) to show that the frequency with which these words are used in modern language predicts their rate of replacement over thousands of years of Indo-European language evolution. Across all 200 meanings, frequently used words evolve at slower rates and infrequently used words evolve more rapidly. This relationship holds separately and identically across parts of speech for each of the four language corpora, and accounts for approximately 50% of the variation in historical rates of lexical replacement. We propose that the frequency with which specific words are used in everyday language exerts a general and law-like influence on their rates of evolution. Our findings are consistent with social models of word change that emphasize the role of selection, and suggest that owing to the ways that humans use language, some words will evolve slowly and others rapidly across all languages.

Multimodel assessment of the factors driving stratospheric ozone evolution over the 21st century

The evolution of stratospheric ozone from 1960 to 2100 is examined in simulations from 14 chemistry‐climate models, driven by prescribed levels of halogens and greenhouse gases. There is general agreement among the models that total column ozone reached a minimum around year 2000 at all latitudes, projected to be followed by an increase over the first half of the 21st century. In the second half of the 21st century, ozone is projected to continue increasing, level off, or even decrease depending on the latitude. Separation into partial columns above and below 20 hPa reveals that these latitudinal differences are almost completely caused by differences in the model projections of ozone in the lower stratosphere. At all latitudes, upper stratospheric ozone increases throughout the 21st century and is projected to return to 1960 levels well before the end of the century, although there is a spread among models in the dates that ozone returns to specific historical values. We find decreasing halogens and declining upper atmospheric temperatures, driven by increasing greenhouse gases, contribute almost equally to increases in upper stratospheric ozone. In the tropical lower stratosphere, an increase in upwelling causes a steady decrease in ozone through the 21st century, and total column ozone does not return to 1960 levels in most of the models. In contrast, lower stratospheric and total column ozone in middle and high latitudes increases during the 21st century, returning to 1960 levels well before the end of the century in most models.

Paralog re-emergence: a novel, historically contingent mechanism in the evolution of antimicrobial resistance

Evolution of resistance to drugs and pesticides poses a serious threat to human health and agricultural production. CYP51 encodes the target site of azole fungicides, widely used clinically and in agriculture. Azole resistance can evolve due to point mutations or overexpression of CYP51, and previous studies have shown that fungicide-resistant alleles have arisen by de novo mutation. Paralogs CYP51A and CYP51B are found in filamentous ascomycetes, but CYP51A has been lost from multiple lineages. Here, we show that in the barley pathogen Rhynchosporium commune, re-emergence of CYP51A constitutes a novel mechanism for the evolution of resistance to azoles. Pyrosequencing analysis of historical barley leaf samples from a unique long-term experiment from 1892 to 2008 indicates that the majority of the R. commune population lacked CYP51A until 1985, after which the frequency of CYP51A rapidly increased. Functional analysis demonstrates that CYP51A retains the same substrate as CYP51B, but with different transcriptional regulation. Phylogenetic analyses show that the origin of CYP51A far predates azole use, and newly sequenced Rhynchosporium genomes show CYP51A persisting in the R. commune lineage rather than being regained by horizontal gene transfer; therefore, CYP51A re-emergence provides an example of adaptation to novel compounds by selection from standing genetic variation.

Detecting regular sound changes in linguistics as events of concerted evolution

Background: Concerted evolution is normally used to describe parallel changes at different sites in a genome, but it is also observed in languages where a specific phoneme changes to the same other phoneme in many words in the lexicon—a phenomenon known as regular sound change. We develop a general statistical model that can detect concerted changes in aligned sequence data and apply it to study regular sound changes in the Turkic language family. Results: Linguistic evolution, unlike the genetic substitutional process, is dominated by events of concerted evolutionary change. Our model identified more than 70 historical events of regular sound change that occurred throughout the evolution of the Turkic language family, while simultaneously inferring a dated phylogenetic tree. Including regular sound changes yielded an approximately 4-fold improvement in the characterization of linguistic change over a simpler model of sporadic change, improved phylogenetic inference, and returned more reliable and plausible dates for events on the phylogenies. The historical timings of the concerted changes closely follow a Poisson process model, and the sound transition networks derived from our model mirror linguistic expectations. Conclusions: We demonstrate that a model with no prior knowledge of complex concerted or regular changes can nevertheless infer the historical timings and genealogical placements of events of concerted change from the signals left in contemporary data. Our model can be applied wherever discrete elements—such as genes, words, cultural trends, technologies, or morphological traits—can change in parallel within an organism or other evolving group.

Entrepreneurial failure and economic crisis: an historical perspective

This chapter analyses the major UK economic crises that have occurred since the speculative bubbles of the seventeenth century. It integrates insights from economic history and business history to analyse both the general economic conditions and the specific business and financial practices that led to these crises. The analysis suggests a significant reinterpretation of the evidence – one that questions economists’ conventional views.