bluuebunny/crossref_metadata_2025 huggingface dataset:
Critical Behaviour in Confined Systems
Authors: Chimowitz Eldred H.
Published: November 2020

The prediction of properties in complex materials is a problem of importance in many applications in chemical and materials engineering; by the term “complex material” we mean a heterogeneous substance, like a porous material containing a confined fluid. Such materials appear in many technological applications, including: (1) processes using supercritical fluids to dry porous aeorogels and thin films [1], (2) physical adsorption of trace components from gaseous effluents, (3) gas storage using microporous materials [2], and (4) chemical separation using inorganic membranes [3]. Inorganic membranes are often highly porous and randomly structured materials with large surface areas available for adsorption, a property that makes them useful in chemical separation and as catalyst supports. In addition to their heterogeneity, complex materials have another distinguishing characteristic that relates to the structure of the heterogeneity itself. Is it periodic, or is it dispersed throughout in some random fashion? These two situations are quite distinct and may, in each instance, show critical behavior for a confined fluid belonging to entirely different universality classes, an issue that to the present time is still unsettled in the literature. In this chapter, we investigate the critical properties of fluids confined in randomly structured host materials like that found in porous silicon. The main question we address is: how does confinement in a porous structure affect the critical point or phase behavior of a fluid mixture? Before investigating some of the more advanced ideas in this area, we look at the basic thermodynamics of interfaces, and the phenomenon of capillarity in a single idealized pore structure. This simple example provides the impetus for a more detailed study of confinement effects. Consider two phases in equilibrium separated by an interface. The total energy of the composite system is the sum of the energy of each phase plus the energy associated with the interface. In formulating the fundamental thermodynamic equation for energy in this system, we presume that the formation of an interface requires energy; therefore, the energy equation must reflect this fact.
Macronutrients—Phosphorus and Potassium
Authors: Keefer Robert F.
Published: November 2020

Plants have a P concentration between 0.03 and 0.70%, but the usual amount is between 0.1 and 0.4%. Phosphorus is found in every living cell of a plant and is involved in genetic transfer and energy relationships. The actively growing parts, that is, stem tips, new leaves, and new roots, need much P. Seeds, especially at maturity, also have a rich supply of P acting as reserve food. Phosphorus is used in plants for (a) root development—especially the lateral and fibrous roots; (b) cell division—energy for metabolism; (c) reproduction—flowering, fruiting, seed formation all controlled by nucleic acids; (d) maturation—counteracts the ill effects of excessive N fertilization; arid (e) disease resistance— especially important in root rots of seedlings. Plant P is a major constituent of chromosomes present as DNA (deoxyribonucleic acid) used in reproduction and RNA (ribonucleic acid) used in growth processes. Plant P is also a constituent of adenosine triphosphate (ATP) that stores energy for plant use, along with many other phosphate compounds, such as phytin (inositol hexaphosphate) stored in seeds, phospholipids in the chloroplasts, and complexes of sugars, sugar amines, aldehydes, amides, and acids—all involved in plant metabolism. Deficiency of P is not striking or characteristic and is difficult to diagnose. The older leaves may be dark bluish-green, bronze, or purple. The stalks are thin, leaves small, limited lateral growth, delayed maturity, and defoliate prematurely. Probably the most obvious symptom would be the purple coloration, but this is exhibited by only a limited number of plants. The best way to determine if a plant is deficient in P would be to conduct a plant tissue test. If the P level is lower than 0.2% P, then P probably is deficient and the soil in which the plant is growing would benefit from P fertilization. . . . Phosphorus Toxicity? . . . Phosphorus toxicity has not been observed in the field and has only been evident in greenhouse culture solutions when P was present at extremely high concentrations.
Age-Specific Population Models: Steady States and Comparative Statics
Authors: Chu C. Y. Cyrus
Published: November 2020

Mainstream demographers studying the pattern of human population are used to classifying people by their ages. In the terminology of branching processes, the type space of the stochastic process is a subset of positive real numbers that characterize human ages. This chapter deals with this case and studies the corresponding steady states and comparative statics. I showed in chapter 2 that the dynamics of any type-specific population structure can be described by the equation Nt = QNt·l and that Q is block-decomposable in the age-specific case. The fact that the northeast block of Q being a zero matrix not only helps us derive the eigen-values and eigenvectors of Q but also helps us characterize the dynamic evolution of the birth size. Let Bt be the size of birth at period t, la = p1 × • • • × pa be the probability that a person can survive to age a, and ma be the average number of births per surviving member aged a. We see that the following accounting identity must hold: which is Lotka’s (1939) well-known renewal equation. is useful for deriving the steady-state age distribution. Given the assumption of a time-invariant fertility function mu, the total size of birth Bt, which is a linear combination of birth sizes of all fertile age groups, naturally grows at a constant rate in the steady state.
Lineage Extinction and Inheritance Patterns
Authors: Chu C. Y. Cyrus
Published: November 2020

Perhaps the most basic biological instincts of all creatures are to survive and to produce offspring. In ancient times, poor hygienic environment and occasional widespread epidemics obviously gave people strong reasons to worry about the possible extinction of their own lineage. But to transform such a worry into a mathematical problem, it is helpful if the upper class of the society, which has the ability and the leisure to think about the problem on an abstract level, also feels the possibility of such an extinction. Indeed, this was the case in eighteenth-century western Europe. The development of the theory of branching processes in fact started with the calculation of the probability of family surname extinction. Mode (1971) argued that one of the reasons for the decay of family names was that “physical comfort and intellectual capacity were necessarily accompanied by a diminution in fertility.” This statement, that parents choose to have fewer children because they want increase their enjoyment of life, seems to be a more suitable characterization of the argument of Becker’s (1991) contemporary household economics. Others, such as Chu and Lee (1994), argued that it was the scourges of war and famine that were responsible for the major rises of mortality in ancient history. Whatever the cause of lineage extinction, as a large proportion of family surnames continued to die out, Francis Galton (1873), one of the founders of the theory of branching processes, presented his concern with lineage extinction on an abstract level: The problem of family surname extinction concerns part (i) of problem 4001; part (ii) is about the distribution of surnames (types), which was the focus of chapter 4 of this book. Problem 4001 did not attract much attention until Agner Krarup Erlang became interested in this problem because his mother’s surname, Krarup, was about to become extinct. Erlang arrived at the solution below. First, we remove the restriction in problem 4001 that a man can have at most five sons, and let pk be the probability of having k surviving male children.
Sex Preferences and Two-Sex Models
Authors: Chu C. Y. Cyrus
Published: November 2020

The demographic models I reviewed in previous chapters are all one-sex models, in which the sex referred to is usually the female. This setting can be justified if we assume either that the life-cycle vital rates (as functions of state variables) for both sexes are the same or that the population dynamics are determined by one sex alone, independent of the possibly relative abundance of the other sex. However, at least for human population, neither assumption is valid. The ratio of newborn girls and newborn boys is close to one, but is less than one for almost all countries in the world. The age-specific mortality rates of women are also lower than those of men worldwide. This is called sexual dimorphism in the demography literature. Such a dimorphism makes the study of two-sex models indispensable. If we look at the male and female vital rates, we find that the differences are small. Despite this small difference, population dynamics derived solely from male vital rates and those derived solely from female vital rates will show ever-increasing differences with the passage of time. Furthermore, because the intrinsic growth rates derived from male and female lines, respectively, are distinct, we cannot avoid the undesirable conclusion that, if we do not incorporate males and females in a unified model, eventually the sex ratio will become either zero or infinity, which is never the case in reality. This is the inconsistency we have to overcome while dealing with population models with two sexes. Another technical difficulty with two-sex modeling has to do with the irreducibility of the state-transition matrix. I mentioned in chapters 2 and 3 that in an age-specific one-sex model, because people older than a particular age, say β, are not fertile anymore, the age group older than β is an absorbing set; hence, our focus of population dynamics can be restricted to the age set [0, β]. This is why we can transform the n × n Leslie matrix to a Lolka renewal equation. In a two-sex model, however, there does not exist a common upper bound for the reproduction of both sexes, for a male older than β can marry a female younger than β and become fertile again.
Motivations and Perspectives
Authors: Pearson Ronald K.
Published: November 2020

This book deals with the relationship between the qualitative behavior and the mathematical structure of nonlinear, discrete-time dynamic models. The motivation for this treatment is the need for such models in computerized, model-based control of complex systems like industrial manufacturing processes or internal combustion engines. Historically, linear models have provided a solid foundation for control system design, but as control requirements become more stringent and operating ranges become wider, linear models eventually become inadequate. In such cases, nonlinear models are required, and the development of these models raises a number of important new issues. One of these issues is that of model structure selection, which manifests itself in different ways, depending on the approach taken to model development (this point is examined in some detail in Sec. 1.1). This choice is critically important since it implicitly defines the range of qualitative behavior the final model can exhibit, for better or worse. The primary objective of this book is to provide insights that will be helpful in making this model structure choice wisely. One fundamental difficulty in making this choice is the notion of nonlinearity itself: the class of “nonlinear models” is defined precisely by the crucial quality they lack. Further, since much of our intuition comes from the study of linear dynamic models (heavily exploiting this crucial quality), it is not clear how to proceed in attempting to understand nonlinear dynamic phenomena. Because these phenomena are often counterintuitive, one possible approach is to follow the lead taken in mathematics books like Counterexamples in Topology (Steen and Seebach, 1978). These books present detailed discussions of counterintuitive examples, focusing on the existence and role of certain critical working assumptions that are required for the “expected results” to hold, but that are not satisfied in the example under consideration. As a specific illustration, the Central Limit Theorem in probability theory states, roughly, that “sums of N independent random variables tend toward Gaussian limits as TV grows large.” The book Counterexamples in Probability (Stoyanov, 1987) has an entire chapter (67 pages) entitled “Limit Theorems” devoted to achieving a more precise understanding of the Central Limit Theorem and closely related theorems, and to clarifying what these theorems do and do not say.
NARMAX Models
Authors: Pearson Ronald K.
Published: November 2020

As noted In Chapter 1, the general class of NARMAX models is extremely broad and includes almost all of the other discrete-time model classes discussed in this book, linear and nonlinear. Because of its enormity, little can be said about the qualitative behavior of the NARMAX family in general, but it is surprising how much can be said about the behavior of some important subclasses. In particular, there are sharp qualitative distinctions between nonlinear moving average models (NMAX models) and nonlinear autoregressive models (NARX models). Since these representations are equivalent for linear models (c.f. Chapter 2), this observation highlights one important difference between linear and nonlinear discrete-time dynamic models. Consequently, this chapter focuses primarily on the structure and qualitative behavior of various subclasses of the NARMAX family, particularly the NMAX and NARX classes. More specifically, Sec. 4.1 presents a brief discussion of the general NARMAX class, defining five important subclasses that are discussed in subsequent sections: the NMAX class (Sec. 4.2), the NARX class (Sec. 4.3), the class of (structurally) additive NARMAX models (Sec. 4.4), the class of polynomial NARMAX models (Sec. 4.5), and the class of rational NARMAX models (Sec. 4.6). More complex NARMAX models are then discussed briefly in Sec. 4.7 and Sec. 4.8 concludes the chapter with a brief summary of the NARMAX class. The general class of NARMAX models was defined and discussed in a series of papers by Billings and various co-authors (Billings and Voon, 1983, 1986a; Leontartis and Billings, 1985; Zhu and Billings, 1993) and is defined by the equation . . . y(k) = F(y(k – 1), . . . , y(k – p), u(k), . . . , u(k – q), e(k – 1), . . . , e(k – r)) + e(k). (4.1) . . . Because this book is primarily concerned with the qualitative input/output behavior of these models, it will be assumed that e(k) = 0 identically as in the class of linear ARMAX models discussed in Chapter 2.
The Art of Model Development
Authors: Pearson Ronald K.
Published: November 2020

The primary objective of this book has been to present a reasonably broad overview of the different classes of discrete-time dynamic models that have been proposed for empirical modeling, particularly in the process control literature. In its simplest form, the empirical modeling process consists of the following four steps: 1. Select a class C of model structures 2. Generate input/output data from the physical process P 3. Determine the model M ∊ C that best fits this dataset 4. Assess the general validity of the model M. The objective of this final chapter is to briefly examine these four modeling steps, with particular emphasis on the first since the choice of the model class C ultimately determines the utility of the empirical model, both with respect to the application (e.g., the difficulty of solving the resulting model-based control problem) and with respect to fidelity of approximation. Some of the basic issues of model structure selection are introduced in Sec. 8.1 and a more detailed treatment is given in Sec. 8.3, emphasizing connections with results presented in earlier chapters; in addition, the problem of model structure selection is an important component of the case studies presented in Secs. 8.2 and 8.5. The second step in this procedure—input sequence design—is discussed in some detail in Sec. 8.4 and is an important component of the second case study (Sec. 8.5). The literature associated with the parameter estimation problem—the third step in the empirical modeling process—is much too large to attempt to survey here, but a brief summary of some representative results is given in Sec. 8.1.1. Finally, the task of model validation often depends strongly on the details of the physical system being modelled and the ultimate application intended for the model. Consequently, detailed treatment of this topic also lies beyond the scope of this book but again, some representative results are discussed briefly in Sec. 8.1.3 and illustrated in the first case study (Sec. 8.2). Finally, Sec. 8.6 concludes both the chapter and the book with some philosophical observations on the problem of developing moderate-complexity, discrete-time dynamic models to approximate the behavior of high-complexity, continuous-time physical systems.
Principles of Development and Evolution
Authors: West-Eberhard Mary Jane
Published: November 2020

So far, I have outlined the general properties of phenotypes, shown how they relate to development, and presented a model of adaptive evolution based on established principles of development and genetics. Now, using this general framework, I can summarize how developmental plasticity facilitates evolution. Jacob (1977) characterized evolution as “tinkering.” It shuffles and recombines what is already there. Frazzetta (1975), in another felicitous comparison with machines, wrote that evolution manages “the gradual improvement of a machine while it is running” (p. 20). Both of these qualities are possible due to characteristics of phenotypes that are not shared with most machines. Tinkering works because the phenotype is made of recombinable modular components that can be turned off and on in different conditions and can function in more than one context, what Gerhart and Kirshner (1997; Kirschner and Gerhart, 1998) call “weak linkage” to any particular use. Improvement without disruption of function works because of the remarkable active flexibility, and redundancy, in the development of parts. As a result of these two qualities—modularity and plasticity—an organism has the unmachinelike ability to respond to a new situation or to a new gene with the production of a new trait, and then to multiply, through reproduction, the ability to produce this trait. Differential reproduction starts the cycle of variation, selection, and cross-generational change that we call evolution—the most unmachinelike process of all. Many reasons have been given to believe that evolutionary change is difficult and even resisted in a well-adapted population (see chapter 1). The evolution of a novel specialization requires that a single lineage persist while undergoing extensive change. The conditions sometimes mentioned as favoring directional evolution, such as strong competition, very different or changing environments, small founder populations, or very long periods of time (see Mayr, 1982b), also favor population extinction. The idea of developmental cohesiveness, outlined in chapter 1, led to the further belief that major developmental change early in ontogeny would be disruptive. The cohesiveness theme persists even though it long has been clear that innovation does not occur exclusively by terminal addition (see chapter 1).
Heterochrony
Authors: West-Eberhard Mary Jane
Published: November 2020

Heterochrony is evolutionary change in the timing of expression of a phenotype trait, that transfers expression of the trait from one life stage or behavioral or physiological phase to another—”the shifting of characters from one part of an ontogeny to another” (Valentine, 1977b, p. 260) or simply “the displacement of characters in time” (Gould, 1977, p. 225). A clear fossil example occurs in monograptids, where there is a temporal shift in the onset of a modified morphology, a life-history modification that is recorded in the structure of the body (figure 13.1). Heterochrony can occur at any level of organization, including the molecular level, where evolutionary changes in the timing of gene expression have been demonstrated, for example, in echinoids and a fibronectin gene of amphibians (Collazo, 1994). Some recent authors (e.g., McKinney and McNamara, 1991; Reilly et al., 1997) define heterochrony as any change in the timing of regulatory events. Most novel traits qualify as heterochrony by this regulatory-timing definition, since virtually all evolutionary change involves change in the timing of developmental events. This regulatorytiming definition of heterochrony leads to a classification of evolutionary change termed panheterochrony by McKinney and McNamara (1991)—a classification of evolutionary transitions that lumps all evolutionary change under the heading of heterochrony. “Because all developmental events occur along a time line, any significant change is likely to result in a heterochrony at some level” (Raff, 1992, p. 211). As expressed by Barbara McClintock in a staff meeting at Cold Spring Harbor Laboratories, “If I could control the time of gene action, I could cause a fertilized snail egg to develop into an elephant. Their biochemistries are not all that different; it's simply a matter of timing”. I will adhere to a classification that divides the effects of regulatory change into their different kinds of effects on phenotypes, in keeping with the general emphasis on phenotypes in this book.
Combinatorial Evolution at the Molecular Level
Authors: West-Eberhard Mary Jane
Published: November 2020

Some of the best evidence for combinatorial evolution comes from studies of molecular evolution. This chapter discusses combinatorial molecular evolution and shows that it is facilitated by the same properties of the molecular phenotype—modularity and flexibility—that facilitate combinatorial evolution at higher levels of organization. This is not a review of molecular or genomic evolution, and I am aware that by the time it is published it will lack the latest references even on the few topics discussed. I suspect that continued progress will only make the main point of this chapter more obvious: in many respects, evolution at the molecular level follows the same pattern as that seen at higher levels of organization, for it involves modular reorganization and developmental plasticity as architects of evolutionary change. A combinatorial view of structural change has long been commonplace in chemistry, since all of the materials of the organic and inorganic world come from different combinations of only 112 elements listed in the periodic table. Since biochemistry and molecular biology focus on the fundamentally modular structure and behavior of biological molecules, it is perhaps not surprising that they arrived early at a combinatorial view of evolution, and that it was a molecular biologist (Jacob, 1977) who described evolution as “tinkering” with preexisting pieces. The lowest level of combinatorial evolution is based on the “changeability” of the genetic code— its ability to undergo rearrangement without loss of functionality (Maeshiro and Kimura, 1998). A reorganizational basis for some kinds of mutation was also proposed by premolecular geneticists like H. J. Muller (see discussion of this work in Huxley, 1942, p. 92), who saw minute rearrangements as a kind of mutation distinguishable from “substantive” change of the chromosomal-damage type caused by ultraviolet radiation. More recently, Dickinson (1988) refers to a “combinatorial” model for the evolution of gene regulation. And genetic engineering makes extensive use of combinatorial principles in creating novel substances and genes.
Assessment
Authors: West-Eberhard Mary Jane
Published: November 2020

A book on developmental plasticity needs a chapter on assessment, if only to show that adaptive environmental assessment occurs. Skepticism regarding the ability of nonhuman organisms to assess conditions well enough to make adaptive decisions has a long history in evolutionary biology, and it has been an important barrier to understanding the evolution of adaptive developmental plasticity. It is worth briefly reviewing this history in order to understand certain preconceptions about assessment that still persist. In the nineteenth century, critics of Darwin’s theory of sexual selection (Darwin, 1871) balked at the idea of an “aesthetic sense” in lowly creatures that would enable female choice of mates (representative papers are reprinted and discussed in Bajema, 1984). Later, the barrier persisted for other reasons. Even though naturalists routinely used the condition-appropriate expression of phenotypic traits to support adaptation hypotheses—a practice that assumes adaptive assessment of conditions as it is defined here—theoretically inclined biologists paid little attention to the question of facultatively expressed traits. Part of the difficulty lay in the problem of explaining how adaptive assessment could evolve within the framework of conventional genetics. Theodosius Dobzhansky, one of the twentieth century’s leading evolutionary biologists, acknowledged this unresolved problem in remarks following a lecture by J. S. Kennedy on the phase polyphenisms of migratory locusts (Kennedy, 1961). Dobzhansky referred to the “challenge to a geneticist” of explaining the adaptive switch between the sedentary and the migratory phenotypes of the locusts, which had been shown to be largely independent of genotype. He suggested that an extrachromosomal factor may be involved, a symbiotic microorganism that acts as a “plasmagene” whose multiplication would eventually stimulate phase change. Although Dobzhansky’s proposal was no more preposterous than some of the regulatory devices that have actually been discovered, Kennedy (1961) minced no words in his reply to this suggestion: . . . [W]e need not feel obliged to invoke a second organism to explain [phase polymorphism] unless we are reluctant to concede an important part to the environment as well as to heredity in moulding development. . . .
Enzyme Inhibition
Authors: Frey Perry A. , Hegeman Adrian D.
Published: November 2020

One aspect of the importance of enzymes in biology can be appreciated by considering the attention that continues to be focused on the inhibition of enzymatic activity. Historically, inhibitors played important roles in the elucidation of metabolic pathways. An example was the use of malonate as a metabolic inhibitor, leading to the accumulation of succinate in metabolizing cell extracts. Malonate proved to be an inhibitor of succinate dehydrogenase, and its effect on metabolism revealed the importance of succinate as a metabolic intermediate and of succinate dehydrogenase in metabolism. In this way, malonate as an inhibitor played an important role in the elucidation of the tricarboxylic acid cycle. Countless competitive inhibitors have been applied in various ways to the characterization of active sites. Clues to the binding properties and specificities of active sites can be deduced by systematically varying the structures of competitive inhibitors and comparing the inhibition constants. In another application, competitive inhibitors are often used to shield active sites against the effects of group selective chemical modification. Because biological processes are catalyzed by enzymes, inhibitors can be used to manage biochemical dynamics to the advantage of humans. Examples include pharmaceutical agents and agricultural insecticides and herbicides, which are often inhibitors of specific enzymes. Many targets for ethical drugs are enzymes. For these reasons, the development of enzyme inhibitors is an important objective in pharmaceutical and agricultural research and development. We explained the simplest kinetic properties of reversible inhibitors in chapter 2, and in chapter 1, we discussed the use of competitive reversible inhibitors and affinity-labeling agents for characterizing active sites. The importance of inhibitors in the pharmaceutical and agricultural industries has led to the discovery and invention of compounds that inhibit enzymes by special mechanisms and with very high binding affinities. These inhibitors often displayed special kinetic properties, which led to the development of kinetic paradigms, including slow-binding inhibition and tight-binding inhibition. In chapter 1, we introduced the theoretical significance of transition-state analogs as potent inhibitors of enzymes, and this theory has led to practical applications in the design of inhibitors. In this chapter, we consider some of the special applications of inhibitors in the pharmaceutical and agricultural industries.
Isomerization
Authors: Frey Perry A. , Hegeman Adrian D.
Published: November 2020

Isomerization reactions are important in metabolism to potentiate further transformations that would otherwise be chemically impossible. A familiar example from glycolysis is phosphohexose isomerase, which catalyzes the interconversion of D-glusose-6-P and D-fructose-6-P. The formation of fructose-6-P makes it chemically feasible at a later step of glycolysis to cleave the six-carbon sugar into two three-carbon sugars, glyceraldehyde-3-P, and dihydroxyacetone-P by aldolase. No such cleavage of glucose-6-P into two three-carbon sugars is possible. The dihydroxyacetone-3-P is converted into glyceraldehyde-3-P by another isomerase, triosephosphate isomerase. In this way, glucose-6-P can be transformed into two molecules of glyceraldehyde-3-P, which can then be metabolized through glycolysis to pyruvate. Both reactions of phosphohexose and triosephosphate isomerases involve aldose/ketose interconversions and proceed by similar chemical mechanisms. Other important isomerases include phosphomutases, epimerases, racemases, and carbon-skeleton mutases, all of which have their roles in metabolism. The chemical mechanisms vary with the classes of isomerases and include enolizations, hydride transfer, oxidation/reduction, phosphotransfer, and radical rearrangements. In this chapter, we consider the mechanisms by which enzymes catalyze isomerization reaction. The interconversions of glucose-6-P and fructose-6-P and of the triose phosphates can be formulated chemically. The transformation in is an internal oxidation-reduction, in which the aldehyde group of the aldose is reduced and the neighboring alcoholic group is oxidized. This reaction can take place by either of two chemical mechanisms: an initial enolization at C2 to produce an enediolate intermediate that can be protonated at C1 to produce the product or a direct hydride transfer from C2 to C1. These mechanisms are outlined in scheme 7-1. Loss of the proton C2(H) by enolization in the upper pathway leads to the enediolate intermediate, and return of the proton to C1 (black arrows in scheme 7-1) leads to the ketose product. The hydride transfer mechanism in the lower pathway begins with the dissociation of the alcoholic proton to form the alcoholate intermediate. The alcoholate provides the driving force for the 1,2-hydride transfer (colored arrows in scheme 7-1) accompanied by protonation of the oxygen at C1. The two mechanisms require different hydrogen transfer regimes.
A Case Study of Planning
Authors: Boarnet Marlon , Crane Randall C.
Published: November 2020

The facts, figures, and inferences in chapter 7 regarding municipal behavior toward transit-oriented housing opportunities illustrate many points. Still, there is much that even a careful statistical analysis might miss or misunderstand. For that reason, we also explored what we could learn by talking to real planners about these issues. The case of San Diego is interesting and useful for several reasons. First, the San Diego Trolley is the oldest of the current generation of light rail projects in the United States. Unlike many newer systems, the age of San Diego’s rail transit (the South Line opened in 1981) allows time for land use planning to respond to the fixed investment. Second, the San Diego system is no stranger to modern transit-based planning ideas. The San Diego City Council approved a land-use plan for their stations that includes many of the ideas promoted by transit-oriented development (TOD) advocates (City of San Diego, 1992). Third, the light rail transit (LRT) authority in San Diego County, the Metropolitan Transit Development Board (MTDB), is often regarded as one of the more successful municipal LRT agencies. The initial parts of the MTDB rail transit system were constructed strictly with state and local funds, using readily available, relatively low-cost technology (Demoro and Harder, 1989, p. 6). Portions of San Diego’s system have high fare-box recovery rates, including the South Line, which in its early years recovered as much as 90 percent of operating costs at the fare box (Gómez-Ibáñez, 1985). All of these factors make San Diego potentially a “best-case” example of TOD implementation. When generalizing from this case study, it is important to remember that the transit station area development process in San Diego is likely better developed than in many other urban areas in the United States. The results from San Diego County can illustrate general issues that, if they have not already been encountered, might soon become important in other urban areas with rail transit systems. Also, given San Diego County’s longer history of both LRT and TOD when compared with most other regions, any barriers identified in San Diego County might be even more important elsewhere.
Introduction
Authors: Tinker Peter B. , Nye Peter
Published: November 2020

The art and study of plant nutrition go back at least to Roman times, as essential parts of the business of producing food. This long historical perspective can usefully be studied now, when plant nutrition is largely a matter of science in its principles, but still, to a surprising extent, an art in its application, even in developed countries. In the past, the delay between a scientific advance and the application in practical agriculture was usually many decades. Thus, the rates of fertilizer used by Lawes (Johnston 1994) in experiments in 1850 were not applied widely in practice until after 1950. The movement to precision agriculture may now take the final step to a full science-based nutrition of plants in the field. For these reasons, we have thought it worthwhile to give a highly condensed outline of the history of scientific advance in our subject. It is now generally accepted that under given growth conditions, uptake of a solute by roots is related to its concentration in the soil solution and the extent to which this, in turn, is buffered by the soil. Though these apparently simple ideas were advanced more than a century and a half ago, only recently have they been defined clearly enough to form a basis for detailed understanding of the effect of solutes on plants grown in the soil. These ideas have, in particular, been obscured by specific effects of roots with their associated rhizosphere organisms: for roots not only vary widely in their response to solute concentration, but also alter near them the soil properties we measure in the bulk of the soil. Thus, it is only since the 1950s that we have come within reach of the objective clearly set us by Liebig in 1840 when he wrote: ‘A rational system of agriculture must be based on an exact acquaintance with the means of nutrition of vegetables, and with the influence of soils and action of manure upon them’. The history of ideas about soil and plant relations has been well described by Russell (1937) and Wild (1988) for the period up to the beginning of the twentieth century.
Local Movement of Solutes in Soil
Authors: Tinker Peter B. , Nye Peter
Published: November 2020

In the previous chapter, we dealt with the distribution of solutes between gas, liquid and solid phases in the soil at equilibrium; and with the rates of redistribution between these phases within soil pores. In this chapter, we consider movement of the order of 1 –1000 mm from one volume of soil to another. Such movements occur largely by diffusion and mass flow of the soil solution or soil air, and by mass movement of the body of the soil. Major movements that involve the balance and amount of solutes in the whole soil profile, including plant uptake and drainage losses, are treated in chapter 11. The process of diffusion results from the random thermal motion of ions, atoms or molecules. Consider a long column of unit cross-section orientated along the x axis, and containing a mixture of components in a single phase at constant temperature and external pressure. If the concentration of an uncharged component is greater at section A than at section B, then on average more of its molecules will move from A to B than from B to A. The net amount crossing a unit section in unit time, which is the flux, is given by the empirical relation known as Pick’s first law: . . . F = − D dC/dx (4.1) . . . where F is the flux, and dC/dx is the concentration gradient across the section. The minus sign arises because movement is from high to low concentration in the direction of increasing x. The diffusion coefficient, D, is thus defined by the equation as a coefficient between two quantities, F and dC/dx, which can be measured experimentally. It is not necessarily a constant. The diffusion coefficient of the molecules in a phase is directly proportional to their absolute mobility, u, which is the limiting velocity they attain under unit force. Terms D and u are related by the Nernst-Einstein equation: . . . D = ukT (4.2) . . . where k is the Boltzmann constant and T is the temperature on the Kelvin scale. The Nernst-Einstein equation is derived as follows (Atkins 1986, p. 675).
Doctors and Patients: The Practice(s) of Nymphomania
Authors: Goldberg Ann
Published: November 2020

The peasant Margaretha D., noted the asylum log, “often suffers from hysterical attacks, with which she wants to be treated like a distinguished lady . . . She raises herself above her social position and demands great attention and care.” This patient, in other words, though considered mad by the Eberbach asylum, was not a true hysteric: she rather “played” the hysterical lady. Two important issues suggest themselves from this description of feigned illness. The first has to do with the connection between class, gender, and the representation of illness. Madness, it seems, had its class and gender codes. Certain symptoms of hysteria—which in the eighteenth century had become a fashionable illness of privileged women, signifying the pathologies accompanying luxury, leisure, and “civilization”—appeared suspicious in a poor, peasant woman. Secondly, the “playing” of illness suggests (inadvertently) a subtext, normally buried and only implicit in the asylum notes: of illness as strategic behavior on the part of the patient within the social dynamics of the asylum. Margaretha’s symptoms were at least in part the result of a self-presentation to her keepers, a communicative act, with its own aims—attention, better care, and so forth. Both of these issues—the link between class, gender, and illness, on the one hand, and the strategic nature of symptoms, on the other—are at the core of the following analysis of nymphomania. Nineteenth-century physicians interpreted the behavior of nymphomaniacal women as a function of an internal state of being—as pathologically excited genitals—and in this way, they contributed to the construction of a modern conception of sexuality as an innate essence of personality. While no longer a clinical entity in post-Freudian psychiatry, the image of the out-of-control, sex-obsessed nymphomaniac remains very much alive in popular culture and continues to be grounded in a conception of sexuality as inner essence and “drive.” This analysis, by contrast, looks at nymphomania as acts and attitudes, which took place within very specific social contexts: the power dynamics of the asylum and the doctor-patient relationship.
Independent Artisans
Authors: Gordon Robert B.
Published: November 2020

By 1730 New England colonists needed increasingly large amounts of iron for their expanding economy. Shipsmiths forged iron fastenings used in the vessels they built for the coastal and West Indian trades. The mariners who sailed these ships wanted large, strong iron anchors. Millwrights needed waterwheel axles and gudgeons, spindles, and numerous other iron components for gristmills, sawmills, fulling mills, and oil mills. Builders of the forges and furnaces that smelted and shaped iron products had to have iron hammerheads and forge plates. The pioneers on the frontier in New York and northern New England wanted massive iron kettles for boiling potash, usually the first cash crop they got off their newly cleared land. Everyone needed nails. Building a bloomery forge offered an adventurer in Connecticut’s Western Lands the easiest way to start making iron. One man could run a forge, although a helper made the work easier. The bloomery proprietor needed less capital than would be required for other types of ironworks. The region had plenty of easily developed water privileges of the right size to power a bloomery forge. Although it took skill and practice to make high-quality metal, a forge owner or hired hand could learn enough of the bloom smelting technique from an experienced smith within a few months to make serviceable metal. Iron of ordinary quality satisfied most people’s needs in the early days of the northwest. If the weather were bad, ore or fuel were unavailable, crops demanded attention, or the market of iron were slow, the proprietor could easily shut down his forge at short notice and restart it as soon as conditions improved. Although a bloomery forge could be part of an enterprise employing fifty or more hands, it could also be little more than a smithy in size and complexity. A farmer could accumulate enough money to build one. Alternatively, a number of individuals might take shares in a forge run by a single artisan. The proprietors of a mercantile business, or of grist or sawmills on the same or a nearby water privilege, could easily add a bloomery to their other enterprises.
Substance and Function in Chemical Research
Authors: Rothbart Daniel
Published: November 2020

When chemical instruments are used in the laboratory, a specimen undergoes changes at the microscopic level. Depending on the instrument, the specimen absorbs or emits radiation. Alternatively, radiation is scattered, refracted, or diffracted. We often read that microscopic events produced from chemical instrumentation are real, as opposed to mere artifacts of the experiment. But exactly what does this mean? This philosophical question underlies a continual dilemma for the experimental chemist, whether to declare triumphantly that his/her findings reveal some insight about a chemical substance or to refrain from such a judgment for fear of having produced a mere artificial effect. Of course, a commonplace position is that the artificiality of laboratory techniques can be separated, in principle, from the real effects, because these techniques enable scientists to break the influence of laboratory constructions on experimental “ facts.” But some commentators have resurrected the fairly skeptical view that such declarations of success are grossly overstated because the interference from various instrumental techniques, laboratory equipment, and theoretical ideas precludes the possibility of exposing properties of independently existing substance. If we address this philosophical question by exploring techniques of chemical instrumentation, we find that the categories of a laboratory artifact and real effect are not mutually exclusive. As I argue here, the experimental phenomena of chemical research are both real and artificially produced from laboratory apparatus, manufactured conditions, and sophisticated techniques of researchers. The plan of this chapter is as follows: examine the character of analytical instruments in chemistry (section 1); explain the difference between an artifact and a real effect (section 2); examine the process of virtual witnessing in chemistry (section 3); explore how instruments are designed to mimic known chemical or physical processes (section 4); introduce the philosophical importance of noise-blocking techniques (section 5); and conclude with brief remarks about experimental reduction (section 6). The similarities and differences between absorption spectroscopy and Raman spectroscopy are discussed. In this chapter I adopt a functional orientation to our understanding chemical substance, according to which a specimen is known by those capacities that technicians try to exploit during laboratory research.
Historical Perspectives: What Can We Learn?
Authors: Tammemagi Hans
Published: November 2020

More than any other single event, the seemingly endless wandering of the garbage barge Mobro 4000 symbolizes the frustrating situation we find ourselves in. The barge, laden with refuse from the town of Islip on Long Island, New York, set sail on March 22,1987, and roamed for 55 days from port to port down the Atlantic seaboard, along the coast of Central America, and into the Caribbean in search of a place that would accept its smelly load. None would. Eventually, after having traveled more than 9,600 kilometers, the barge returned to New York, where the waste was finally incinerated and the ashes placed in a landfill. A garbage crisis is at hand. The situation has not improved since the Mobro incident. As a society we are generating far too much waste, especially in North America. At the same time, places to dispose of it are becoming limited. The public and politicians have recognized the inherent dangers of existing landfills and are refusing to build new ones—or, as in the case of the Mobro, they are refusing to accept any more waste than is necessary. How did we get into such a mess? The first recorded regulations to control municipal waste were implemented during the Minoan civilization, which flourished in Crete from 3000 to 1000 B.C. Solid wastes from the capital, Knossos, were placed in large pits and covered with layers of earth at intervals (Wilson, 1977). This basic method of landfilling has remained relatively unchanged right up to the present day. In Athens, by 500 B.C. it was required that garbage be disposed of at least 1.5 kilometers from the city walls. Each household was responsible for collecting its own garbage and taking it to the disposal site. The first garbage collection service was established during the period of the Roman Empire. Householders tossed their refuse into the streets, and then it was shoveled onto horse-drawn carts and transported to an open pit, often located within the community. The bodies of dead animals (and sometimes people) were buried in pits outside the towns to spare inhabitants their odor.