Entangled: Romantic Love and Philosophy

In order to do philosophy, one must understand what it is. Often one has to develop this understanding on their own, since the philosophical canon has such a range of attitudes, styles, and objects. In this paper, philosophy is a dialogue, a conversation spanning space and time, as well as the inside of one\u27s own head. Philosophy is not something that can provide an absolute truth about reality; rather, philosophy is a means of describing how the philosopher thinks reality ought to be. To exemplify this understanding of philosophy, this paper is written as fiction. It follows two people as they try to determine what romantic love is, and why it was a neglected or minimized philosophical object for centuries. As the characters converse, they develop the concept of philosophy described above, discuss the place of women, passion, and reason in philosophy, and determine – to the extent they are able – that romantic love is something people do, rather than a feeling or state of being, and is based on an unjustifiable attraction to another person and Aristotle\u27s concept of friendship, specifically philia. The idea of romantic love being a practice, rather than an emotion or a state of being, seems to be uncommon in philosophical work on the topic. It seems just as rare, especially historically, to think of romantic love as being between equals, who mutually care for each other and commit equally to the relationship. This paper aims to point out the holes I have found in my reading on romantic love in philosophy and to provide new perspectives on romantic love in the hopes of prompting further and broader discussion on the topic

Field Experiments on Responses of a Freshwater, Benthic Macroinvertebrate Community to Vertebrate Predators

We examined the seasonal importance of vertebrate predators in potentially regulating the abundance and diversity of the benthic macroinvertebrates in the littoral zone of a soft-bottom reservoir that receives thermal effluent from a nuclear production reactor. Thirty-six predator (fish and turtle) exclusion cages (4 m-') were placed in shallow water at six locations along a thermal gradient in Par Pond, a 1100-ha cooling reservoir on the Savannah River Plant near Aiken, South Carolina, USA. An additional 36 control plots (4 m-) were also set up. Cages were in place during three, 3-mo test periods beginning in September 1977. Estimates of benthic density, taxon richness, and distribution within functional groups (defined by feeding mechanism) were calculated for each test period. Effects of temperature on predator-prey relationships were also determined. Experimental results of this study suggest that vertebrate predation was not the fundamental parameter organizing the benthic macroinvertebrate community in the littoral zone of this reservoir. Neither taxon richness nor density of total macroinvertebrates was conclusively related to predator treatment. Relationships between predator treatment and community response (changes in density and taxon richness) were generally unaffected by either plot locality, temperature fluctuations from thermal effluent, or seasonal changes. When data from caged and control plots were pooled, however, both location and water temperature individually had direct impacts on the benthic community. From our results and other field studies we hypothesize that individual species of "keystone" benthic predators (Paine 1969b) do not occur in the littoral zone of freshwater lentic environments with soft bottoms. This hypothesis is based on the following four arguments. First, environmental heterogeneity should reduce predator efficiency relative to that found in rocky intertidal systems where keystone predation may be present. Second, relative food web complexity should reduce the community importance of an individual predator species. Third, the apparent relatively greater resource partitioning of space and food in the freshwater littoral zone hinders monopolization of ratelimiting environmental resources by a single dominant prey species. Fourth, the effects of predation may not be extensive enough in time or area to provide sufficient resource space (and thus food) for exploitation by fugitive species. Possible regulation by a guild of predators and cases where the general hypothesis might be falsified are discussed

Comparison of Computational-Model and Experimental-Example Trained Neural Networks for Processing Speckled Fringe Patterns

The responses of artificial neural networks to experimental and model-generated inputs are compared for detection of damage in twisted fan blades using electronic holography. The training-set inputs, for this work, are experimentally generated characteristic patterns of the vibrating blades. The outputs are damage-flag indicators or second derivatives of the sensitivity-vector-projected displacement vectors from a finite element model. Artificial neural networks have been trained in the past with computational-model-generated training sets. This approach avoids the difficult inverse calculations traditionally used to compare interference fringes with the models. But the high modeling standards are hard to achieve, even with fan-blade finite-element models

Vibrational Analysis of Engine Components Using Neural-Net Processing and Electronic Holography

The use of computational-model trained artificial neural networks to acquire damage specific information from electronic holograms is discussed. A neural network is trained to transform two time-average holograms into a pattern related to the bending-induced-strain distribution of the vibrating component. The bending distribution is very sensitive to component damage unlike the characteristic fringe pattern or the displacement amplitude distribution. The neural network processor is fast for real-time visualization of damage. The two-hologram limit makes the processor more robust to speckle pattern decorrelation. Undamaged and cracked cantilever plates serve as effective objects for testing the combination of electronic holography and neural-net processing. The requirements are discussed for using finite-element-model trained neural networks for field inspections of engine components. The paper specifically discusses neural-network fringe pattern analysis in the presence of the laser speckle effect and the performances of two limiting cases of the neural-net architecture