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Among recent materialists, it has become increasingly common to waive questions of the reducibility or even the consistency of psychological and physiological domains of discourse and to argue for the eliminability of mentalistic conceptions in favor of descriptions of the physical workings of organisms.
A more paradigmatic reductionist account has the advantage of giving a clear standard by which we might judge the acceptability of physicalist views: materialism is correct if physical theory is capable of capturing psychological theory. Arguments over this, the identity theory, unfortunately enmeshed theorists in apparently endless disputes over the viability of topic neutral translations; hence, if it is possible for materialists to argue for their position without maintaining a general reduction, such a maneuver would have much to recommend it.
Tethered mobile robots are ideal for electrically noisy environments and for time-consuming tasks that require robust data communication and uninterrupted power delivery. However, tethers may become entangled in cluttered environments, leading to immobilisation and consequent mission failure. This work addresses real-time monitoring of tethers to detect tether entanglement, perform disentanglement through tether following and localise within line of sight. Experimental hardware is proposed to implement the tether monitoring techniques. Experiments are performed for single and dual mobile robots to search a target environment and entanglement detection is shown to be successful using quantitative metrics such as mean localization error.
Multiple realization historically mandated the autonomy of psychology, and its principled irreducibility to neuroscience. Recently, multiple realization and its implications for the reducibility of psychology to neuroscience have been challenged. One challenge concerns the proper understanding of reduction. Another concerns whether multiple realization is as pervasive as is alleged. I focus on the latter question. I illustrate multiple realization with actual, rather than hypothetical, cases of multiple realization from within the biological sciences. Though they do support a degree of autonomy for higher levels of explanation and organization, they do not have the dire consequences critics of multiple realization fear.
Evolutionary models can explain the dynamics of populations, how genetic, genotypic, or phenotypic frequencies change with time. Models incorporating chance, or drift, predict specific patterns of change. These are illustrated using classic work on blood types by Cavalli-Sforza and his collaborators in the Parma Valley of Italy, in which the theoretically predicted patterns are exhibited in human populations. These data and the models display properties of ensembles of populations. The explanatory problem needs to be understood in terms of how likely an observed change, in either a population or an ensemble, would be under drift alone; this is fundamentally a matter of chance. Understood in this way, issues of drift and chance undercut most recent philosophical, but not biological, discussions of the role of “genetic drift.”
Reverse engineering is a matter of inferring adaptive function from structure. The utility of reverse engineering for evolutionary biology has been a matter of controversy. I offer a simple taxonomy of the uses of engineering design in assessing adaptation, with a variety of illustrations. The plausibility of applications of engineering design reflects the specific way the models are elaborated and derived.
When planning a mutation to test some hypothesis, one
crucial question is whether the new side chain is compatible
with the existing structure; only if it is compatible can
the interpretation of mutational results be straightforward.
This paper presents a simple way of using the sensitive
geometry of all-atom contacts (including hydrogens) to
answer that question. The interactive MAGE/PROBE system
lets the biologist explore conformational space for the
mutant side chain, with an interactively updated kinemage
display of its all-atom contacts to the original structure.
The Autobondrot function in PROBE systematically explores
that same conformational space, outputting contact scores
at each point, which are then contoured and displayed.
These procedures are applied here in two types of test
cases, with known mutant structures. In ricin A chain,
the ability of a neighboring glutamate to rescue activity
of an active-site mutant is modeled successfully. In T4
lysozyme, six mutations to Leu are analyzed within the
wild-type background structure, and their Autobondrot score
maps correctly predict whether or not their surroundings
must shift significantly in the actual mutant structures;
interactive examination of contacts for the conformations
involved explains which clashes are relieved by the motions.
These programs are easy to use, are available free for
UNIX or Microsoft Windows operating systems, and should
be of significant help in choosing good mutation experiments
or in understanding puzzling results.
Parvalbumins constitute a class of calcium-binding
proteins characterized by the presence of several helix-loop-helix
(EF-hand) motifs. In a previous study (Revett SP, King
G, Shabanowitz J, Hunt DF, Hartman KL, Laue TM, Nelson
DJ, 1997, Protein Sci 7:2397–2408), we presented
the sequence of the major parvalbumin isoform from the
silver hake (Merluccius bilinearis) and presented
spectroscopic and structural information on the excised
“EF-hand” portion of the protein. In this study,
the X-ray crystal structure of the silver hake major parvalbumin
has been determined to high resolution, in the frozen state,
using the molecular replacement method with the carp parvalbumin
structure as a starting model. The crystals are orthorhombic,
space group C2221, with a = 75.7 Å,
b = 80.7 Å, and c = 42.1 Å.
Data were collected from a single crystal grown in 15%
glycerol, which served as a cryoprotectant for flash freezing
at −188 °C. The structure refined to a conventional
R-value of 21% (free R 25%) for observed
reflections in the range 8 to 1.65 Å [I
> 2σ(I)]. The refined model includes
an acetylated amino terminus, 108 residues (characteristic
of a β parvalbumin lineage), 2 calcium ions, and 114
water molecules per protein molecule. The resulting structure
was used in molecular dynamics (MD) simulations focused
primarily on the dynamics of the ligands coordinating the
Ca2+ ions in the CD and EF sites. MD simulations
were performed on both the fully Ca2+ loaded
protein and on a Ca2+ deficient variant, with
Ca2+ only in the CD site. There was substantial
agreement between the MD and X-ray results in addressing
the issue of mobility of key residues in the calcium-binding
sites, especially with regard to the side chain of Ser55
in the CD site and Asp92 in the EF site.
Developmental biology has resurfaced in recent years, often without a clearly central role for the organism. The organism is pulled in divergent directions: on the one hand, there is an important body of work that emphasizes the role of the gene in development, as executing and controlling embryological change; on the other hand, there are more theoretical approaches under which the organism disappears as little more than an instance for testing biological generalizations. I press here for the ineliminability of the organism in developmental biology on explanatory grounds. I examine classical work concerned with growth and development, particularly in Drosophila and C. elegans. Some of this work is suggestive of modular development, and accordingly suggests a level below that of the organism as being explanatory. These are not the only type of case. There are other equally well-established results, which indicate greater integration in the developing organism. Though with a modular organization the organism can be thought of as made up of its constituent traits, and though the explanations of these traits may lie in terms of cells or genes, even with modular development the explanations of “genetic” differences require an appeal to the organism. With non-modular organization the organism has an even more central role. This does not mean that these genetic or cellular contributions are unreal in any way, or that development requires some sort of vitalistic contribution; but the genetic contributions make sense only as constituents of the organism, embedded in a larger organic context.
Genetic regulatory networks are complex, involving tens or hundreds of genes and scores of proteins with varying dependencies and organizations. This invites the application of artificial techniques in coming to understand natural complexity. I describe two attempts to deploy artificial models in understanding natural complexity. The first abstracts from empirically established patterns, favoring random architectures and very general constraints, in an attempt to model developmental phenomena. The second incorporates detailed information concerning the genetic structure, organization, and dependencies in actual systems in an attempt to explain developmental differences. The results offered by these models, pitched at these different levels of abstraction, are different. The more detailed models are more continuous with classical developmental approaches.
Sober (1992) has recently evaluated Brandon's (1982, 1990; see also 1985, 1988) use of Salmon's (1971) concept of screening-off in the philosophy of biology. He critiques three particular issues, each of which will be considered in this discussion.