Sharing, Gift-Giving, and Optimal Resource Use Incentives in Hunter-Gatherer Society

In the typical hunter-gatherer society, decision-making is collective, yet decentralized, access to resources is shared, goods are typically distributed via reciprocal exchange, sharing, and gift-giving, and the distribution of both income and decision-making power is egalitarian. We argue these features are interrelated. We adopt an incentive-based view of sharing and gift-giving, in which the fundamental role of sharing and gift-giving is to implement socially desirable production decisions in the face of a common resource use problem. We show how this system decentralizes decision-making, while at the same time encouraging agents to make production decisions in the best interests of the group. Sharing rules give agents optimal use incentives, while gift-giving obligations give agents incentives to reveal private information about skill. The system has some interesting properties; for example, it may result in a relatively equal distribution of income, even though the productive capabilities of agents differ. Our theory is also able to account for some features of the ethnographic record that do not jibe well with existing theories of sharing; for example, why the rather extensive free-riding on the efforts of the most productive agents is typically tolerated in hunter-gatherer society.

Marriage, Specialization, and the Gender Division of Labor

A customary gender division of labor is one in which women and men are directed towards certain tasks and/or explicitly prohibited from performing others. We offer an explanation as to why the gender division of labor is so often enforced by custom, and why customary gender divisions of labor generally involve both direction and prohibition. Our model builds on the literature on the marital hold-up problem, and considers both problems in choice of specialty and human capital acquisition in a framework in which agents learn a variety of skills and must search for a marriage partner on the marriage market. We show that wasteful behavior may emerge due to strategic incentives in career choice and human capital acquisition, and that both problems may be mitigated through the customary gender division of labor. We find, however, that a gender division of labor is not Pareto-improving; one gender is made worse off. Both the distributional effects and welfare gains to a customary gender division of labor decrease as opportunities to exchange in markets increase.

A Human Capital-Based Theory of Post Marital Residence Rules

In pre-modern societies the residence of a newly-wedded couple is often decided by custom. We formulate a theory of optimal post-marital residence rules based on contracting problems created by the nature of pre-marriage human capital investments. We argue that a fixed post-marital residence rule may mitigate a hold-up problem by specifying marriage terms and limiting possibilities for renegotiation; the trade-off is that the rule may prohibit beneficial renegotiation of post-marital location. A point of interest of our approach is that the magnitude and direction of transfers accompanying marriage are endogenous. We apply our theoretical results to understanding cross-cultural post-marital residence patters. We find some predictive ability in variables related to outside options, control over the environment, and potential degree of social control.Marriage, Bargaining, Hold-up Problem, Dowry, Bride-Price

Simulation and inference algorithms for stochastic biochemical reaction networks: from basic concepts to state-of-the-art

Stochasticity is a key characteristic of intracellular processes such as gene regulation and chemical signalling. Therefore, characterising stochastic effects in biochemical systems is essential to understand the complex dynamics of living things. Mathematical idealisations of biochemically reacting systems must be able to capture stochastic phenomena. While robust theory exists to describe such stochastic models, the computational challenges in exploring these models can be a significant burden in practice since realistic models are analytically intractable. Determining the expected behaviour and variability of a stochastic biochemical reaction network requires many probabilistic simulations of its evolution. Using a biochemical reaction network model to assist in the interpretation of time course data from a biological experiment is an even greater challenge due to the intractability of the likelihood function for determining observation probabilities. These computational challenges have been subjects of active research for over four decades. In this review, we present an accessible discussion of the major historical developments and state-of-the-art computational techniques relevant to simulation and inference problems for stochastic biochemical reaction network models. Detailed algorithms for particularly important methods are described and complemented with MATLAB implementations. As a result, this review provides a practical and accessible introduction to computational methods for stochastic models within the life sciences community

CFD Simulation of Flow through Packed Beds using the Finite Volume Technique

When a disordered packed bed, or any heterogeneous media is studied using computational fluid dynamics, the tortuous task of generating a domain and creating a workable mesh presents a challenging issue to Engineers and Scientists. In this Thesis these challenges are addressed in the form of three studies in which both traditional and novel techniques are used to generate packed beds of spheres and cylinders for analysis using computational fluid dynamics, more specifically, the finite volume method. The first study uses a Monte-Carlo method to generate random particle locations for use with a traditional CADbased meshing approach. Computational studies are performed and compared in detail with experimental equivalent beds. In the second study, where there is a need for actual, physical beds to be studied, magnetic-resonance-imaging is used coupled with a novel approach known as image based meshing. In parallel experimental studies are performed on the experimental bed and compared with computational data. In the third study, to overcome fidelity issues with the previous approaches, a physical packed bed is manufactured which is 100% geometrically faithful to its computational counterpart to provide a direct comparison. All three computational studies have shown promising results in comparison with the experimental data described in this Thesis, with the data of Reichelt (1972) and the semi-empirical correlation of Eisfeld & Schnitzlein (2001). All experiments and computational models were carried out by the author unless otherwise stated

Technological Progress, Population Growth, Property Rights, and the Transition to Agriculture

Following the rapidly growing literature on the Neolithic revolution, I develop a model of mankind’s initial transition to agriculture in which population and technological sophistication are both endogenous variables. I assume that total factor productivity in both agriculture and hunting and gathering depend on natural resource endowments and a general purpose technology, but that TFP in agriculture is relatively more dependent on technological sophistication than TFP in hunting and gathering, and that agriculture requires effort be expended in land enclosure. The model describes combinations of population pressure, technological sophistication, and resource endowments that are sufficient to generate a switch to agriculture and enclosure, but also admits the possibility that no switch will occur. I estimate the steady-state relationships of the model by applying a two-state, two-equation model with endogenous regime switching using information on the incidence of agriculture, population density, technology, and environment among 186 pre-modern societies. I find that habitat diversity, a relatively flat landscape, and exceptionally heavy rainfall are among factors contributing to total factor productivity in hunting and gathering, while soil quality, climate suitability and proximity to an ocean increase total factor productivity in agriculture. I also estimate that roughly ten percent of TFP in agriculture can be attributed to technological sophistication, while TFP in hunting and gathering is not influenced by technology. Among other things, I find evidence that endogenous growth effects may be responsible for approximately 40% of observed technological sophistication among agricultural societies, but do not appear important among hunter-gatherers

Can mid-infrared biomedical spectroscopy of cells, fluids and tissue aid improvements in cancer survival? : a patient paradigm

This review will take a fresh approach from the patient perspective; offering insight into the applications of mid-infrared biomedical spectroscopy in a scenario whereby the patient presents with non-specific symptoms and via an extensive diagnostic process multiple lesions are discovered but no clear sign of the primary tumour; a condition known as cancer of unknown primary (CUP). With very limited options to diagnose the cancer origin, treatment options are likely to be ineffective and prognosis is consequentially very poor. CUP has not yet been targeted by infrared biospectroscopy, however, this timely, concise dissemination will focus on a series of research highlights and breakthroughs from the field for the management of a variety of cancer-related diseases - many examples of which have occurred within this year alone. The case for integration of mid-infrared (MIR) technology into clinical practice will be demonstrated largely via diagnostic, but also therapeutic and prognostic avenues by means of including cytological, bio-fluid and tissue analysis. The review is structured around CUP but is relevant for all cancer diagnoses. Infrared spectroscopy is fast developing a reputation as a valid and powerful tool for the detection and diagnosis of cancer using a variety of sample formats. The technology will produce data and tools that are designed to complement routine clinical practice; enhancing the ability of the clinician to make a reliable and non-subjective decision and enabling decreased levels of mortality and morbidity and gains in patient quality of life