[Introduction to] Plato, Aristotle, and the Purpose of Politics

In this book, Kevin M. Cherry compares the views of Plato and Aristotle about the practice, study, and, above all, the purpose of politics. The first scholar to place Aristotle\u27s Politics in sustained dialogue with Plato\u27s Statesman, Cherry argues that Aristotle rejects the view of politics advanced by Plato\u27s Eleatic Stranger, contrasting them on topics such as the proper categorization of regimes, the usefulness and limitations of the rule of law, and the proper understanding of phronēsis. The various differences between their respective political philosophies, however, reflect a more fundamental difference in how they view the relationship of human beings to the natural world around them. Reading the Politics in light of the Statesman sheds new light on Aristotle\u27s political theory and provides a better understanding of Aristotle\u27s criticism of Socrates. Most importantly, it highlights an enduring and important question: Should politics have as its primary purpose the preservation of life, or should it pursue the higher good of living well?https://scholarship.richmond.edu/bookshelf/1149/thumbnail.jp

Aristotle on Democracy and Democracies

It is a commonplace that Aristotle, like his teacher Plato, was a critic of democracy. This is, to a certain extent, true: Plato and Aristotle both saw democracy, at least as practiced in Athens, as prone to tumultuousness and imprudence. The failed Sicilian expedition, the execution of Socrates, the failure to heed Demosthenes\u27s warnings about Philip of Macedon and Aristotle\u27s own reported flight from Athens all highlighted the weaknesses of Athenian democratic institutions. Yet Aristotle\u27s understanding of political science requires him to consider not only what the simply best regime might be, as Socrates purports to do in the Republic, but also the characteristic advantages and disadvantages of all kinds of regimes, including democracy. This is, in fact, particularly true with regard to democracy: Aristotle suggests that it is unlikely that any regime other than democracy will come into being (Pol. 1286620-22) and, insofar as his political science is intended to be practical, understanding its strengths and limitations is of great importance

Politics and Philosophy in Aristotle\u27s Critique of Plato\u27s Laws

Whether on matters of politics or physics, Aristotle\u27s criticism of his predecessors is not generally considered a model of charitable interpretation. He seems to prefer, as Christopher Rowe puts it, polemic over accuracy (2003, 90). His criticism of the Laws is particularly puzzling: It is much shorter than his discussion of the Republic and raises primarily technical objections of questionable validity. Indeed, some well-known commentators have concluded the criticisms, as we have them in the Politics, were made of an earlier draft of the Laws and that Plato, in light of these criticisms, revised the final version. I hope to suggest, however, that these incongruities should lead us to look beyond Aristotle\u27s explicit criticisms to an issue he also omits while discussing the Republic, namely, the character of philosophy and its place in political life

A Series of Footnotes to \u3ci\u3ePlato\u27s Philosophers\u3c/i\u3e

In her magisterial Plato\u27s Philosophers, Catherine Zuckert presents a radically new interpretation of Plato\u27s dialogues. In doing so, she insists we must overcome reading them through the lens of Aristotle, whose influence has obscured the true nature of Plato\u27s philosophy. However, in her works dealing with Aristotle\u27s political science, Zuckert indicates several advantages of his approach to understanding politics. In this article, I explore the reasons why Zuckert finds Aristotle a problematic guide to Plato\u27s philosophy as well as what she sees as the character and benefits of Aristotle\u27s political theory. I conclude by suggesting a possible reconciliation between Zuckert\u27s Aristotle and her Plato, insofar as both the Socrates whom Plato made his hero and Aristotle agree that political communities will rarely direct citizens toward virtue by means of law and that we must instead look to informal means of doing so

Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks

From bacteria following simple chemical gradients to the brain distinguishing complex odour information, the ability to recognize molecular patterns is essential for biological organisms. This type of information-processing function has been implemented using DNA-based neural networks, but has been limited to the recognition of a set of no more than four patterns, each composed of four distinct DNA molecules. Winner-take-all computation has been suggested as a potential strategy for enhancing the capability of DNA-based neural networks. Compared to the linear-threshold circuits and Hopfield networks used previously, winner-take-all circuits are computationally more powerful, allow simpler molecular implementation and are not constrained by the number of patterns and their complexity, so both a large number of simple patterns and a small number of complex patterns can be recognized. Here we report a systematic implementation of winner-take-all neural networks based on DNA-strand-displacement reactions. We use a previously developed seesaw DNA gate motif, extended to include a simple and robust component that facilitates the cooperative hybridization that is involved in the process of selecting a ‘winner’. We show that with this extended seesaw motif DNA-based neural networks can classify patterns into up to nine categories. Each of these patterns consists of 20 distinct DNA molecules chosen from the set of 100 that represents the 100 bits in 10 × 10 patterns, with the 20 DNA molecules selected tracing one of the handwritten digits ‘1’ to ‘9’. The network successfully classified test patterns with up to 30 of the 100 bits flipped relative to the digit patterns ‘remembered’ during training, suggesting that molecular circuits can robustly accomplish the sophisticated task of classifying highly complex and noisy information on the basis of similarity to a memory

Scaling up molecular pattern recognition with DNA-based winner-take-all neural networks

From bacteria following simple chemical gradients to the brain distinguishing complex odour information, the ability to recognize molecular patterns is essential for biological organisms. This type of information-processing function has been implemented using DNA-based neural networks, but has been limited to the recognition of a set of no more than four patterns, each composed of four distinct DNA molecules. Winner-take-all computation has been suggested as a potential strategy for enhancing the capability of DNA-based neural networks. Compared to the linear-threshold circuits and Hopfield networks used previously, winner-take-all circuits are computationally more powerful, allow simpler molecular implementation and are not constrained by the number of patterns and their complexity, so both a large number of simple patterns and a small number of complex patterns can be recognized. Here we report a systematic implementation of winner-take-all neural networks based on DNA-strand-displacement reactions. We use a previously developed seesaw DNA gate motif, extended to include a simple and robust component that facilitates the cooperative hybridization that is involved in the process of selecting a ‘winner’. We show that with this extended seesaw motif DNA-based neural networks can classify patterns into up to nine categories. Each of these patterns consists of 20 distinct DNA molecules chosen from the set of 100 that represents the 100 bits in 10 × 10 patterns, with the 20 DNA molecules selected tracing one of the handwritten digits ‘1’ to ‘9’. The network successfully classified test patterns with up to 30 of the 100 bits flipped relative to the digit patterns ‘remembered’ during training, suggesting that molecular circuits can robustly accomplish the sophisticated task of classifying highly complex and noisy information on the basis of similarity to a memory

Compiler-aided systematic construction of large-scale DNA strand displacement circuits using unpurified components

Biochemical circuits made of rationally designed DNA molecules are proofs of concept for embedding control within complex molecular environments. They hold promise for transforming the current technologies in chemistry, biology, medicine and material science by introducing programmable and responsive behaviour to diverse molecular systems. As the transformative power of a technology depends on its accessibility, two main challenges are an automated design process and simple experimental procedures. Here we demonstrate the use of circuit design software, combined with the use of unpurified strands and simplified experimental procedures, for creating a complex DNA strand displacement circuit that consists of 78 distinct species. We develop a systematic procedure for overcoming the challenges involved in using unpurified DNA strands. We also develop a model that takes synthesis errors into consideration and semi-quantitatively reproduces the experimental data. Our methods now enable even novice researchers to successfully design and construct complex DNA strand displacement circuits

2D View Aggregation for Lymph Node Detection Using a Shallow Hierarchy of Linear Classifiers

Enlarged lymph nodes (LNs) can provide important information for cancer diagnosis, staging, and measuring treatment reactions, making automated detection a highly sought goal. In this paper, we propose a new algorithm representation of decomposing the LN detection problem into a set of 2D object detection subtasks on sampled CT slices, largely alleviating the curse of dimensionality issue. Our 2D detection can be effectively formulated as linear classification on a single image feature type of Histogram of Oriented Gradients (HOG), covering a moderate field-of-view of 45 by 45 voxels. We exploit both simple pooling and sparse linear fusion schemes to aggregate these 2D detection scores for the final 3D LN detection. In this manner, detection is more tractable and does not need to perform perfectly at instance level (as weak hypotheses) since our aggregation process will robustly harness collective information for LN detection. Two datasets (90 patients with 389 mediastinal LNs and 86 patients with 595 abdominal LNs) are used for validation. Cross-validation demonstrates 78.0% sensitivity at 6 false positives/volume (FP/vol.) (86.1% at 10 FP/vol.) and 73.1% sensitivity at 6 FP/vol. (87.2% at 10 FP/vol.), for the mediastinal and abdominal datasets respectively. Our results compare favorably to previous state-of-the-art methods.Comment: This article will be presented at MICCAI (Medical Image Computing and Computer-Assisted Intervention) 201