295 research outputs found
Marvell's Now
Andrew Marvell’s complex panegyric celebrating Cromwell’s return from Ireland begins with the fateful moment of decision, even if it is not immediately clear to whom the decision belongs (or upon whom it is thrust):
The forward youth that would appear
Must now forsake his muses dear,
Nor in the shadows sing
His numbers languishing.
‘Tis time to leave the books in dust,
And oil the unused armour’s rust:
Removing from the wall
The corslet of the hall. (lines 1-8)
If the subsequent line – “So restless Cromwell could not cease” – identifies the “forward youth” with the man who might be king, the poem initially suggests (as commentators have noted) a different identification: with the poet who now steps out from the shadows, the private and hidden spaces of love poetry and book-filled study, abandoning his erstwhile muses to enter a public space. And this entry is likened to military dressing and engagement. To don the “corslet of the hall” is to take up an armour that not only resides in or decorates the public space but belongs to it, standing metonymically for the kind of engagement
that “must now” be undertaken by both Cromwell and poet. Reading the “So” of line nine as “thus” or “in such a manner” sets the seal on the implied alignment between the poet’s imperative in the present and the political restlessness that drove Cromwell from the “inglorious arts of peace” to “adventurous war” (lines 10-11). Alternatively, reading the
“So” as “therefore” aligns the precocious Cromwell more closely with the “forward” youth, construing the litany of his achievements that follow as exempla, instantiations in the past of the kinds of decision that now, in the historical present, stand before the man again (and by extension face the poet who would appear to record them)
'Thou single wilt prove none': Counting, Succession and Identity in Shakespeare's Sonnets
he need to conjoin singularity and exemplarity drives a range of Shakespeare’s procreation sonnets in the young man sub-sequence. Standing for “a singularly perfect nature” as well as for “the yet more total perfection of the Nature of nature,” as Joel Fineman putsit, the young man “represents not only the particular token and general type of ideality, but, also . . . the harmoniously organic way these are related to one another.” Often, these sonnets achieve their end by projecting the relationship between ideal and actual onto biology; they conflate the metaphysical “pattern” – to borrow a word from Sonnets 19 and 98 –
embodied by the young man with the reproductive generation, potentially
ad infinitum, of his likenesses. This underlying logic derives, as Fineman further notes in passing, from an engagement, more or less explicit, with an inherited mathematical tradition: Only if we grant the unitary arithmetic of idealism does it make sense that the young man, multiplying himself after his own kind, will father the “many” that will prove him “One.” And only if we accept the tidy categoriality of genus and species will we understand how the young man spawns a series of particulars whose lineal succession embodies the young man’s universality: “Proving his
beauty by succession thine.” (251) Fineman’s evidentiary instance comes from Sonnet 2, where the notion of “succession” brings together the biological iteration of sameness with the sequential unfolding of cardinal numbers, “proving” the currency of this “unitary arithmetic” by opening a passage between the idea of a (real) biological series (“like father, like son”) and the series of whole numbers, based on the repeated addition of the idealised unit or the one
Tropical rainforest bird community structure in relation to altitude, tree species composition, and null models in the Western Ghats, India
Studies of species distributions on elevational gradients are essential to
understand principles of community organisation as well as to conserve species
in montane regions. This study examined the patterns of species richness,
abundance, composition, range sizes, and distribution of rainforest birds at 14
sites along an elevational gradient (500-1400 m) in the Kalakad-Mundanthurai
Tiger Reserve (KMTR) of the Western Ghats, India. In contrast to theoretical
expectation, resident bird species richness did not change significantly with
elevation although the species composition changed substantially (<10%
similarity) between the lowest and highest elevation sites. Constancy in
species richness was possibly due to relative constancy in productivity and
lack of elevational trends in vegetation structure. Elevational range size of
birds, expected to increase with elevation according to Rapoport's rule, was
found to show a contrasting inverse U-shaped pattern because species with
narrow elevational distributions, including endemics, occurred at both ends of
the gradient (below 800 m and above 1,200 m). Bird species composition also did
not vary randomly along the gradient as assessed using a hierarchy of null
models of community assembly, from completely unconstrained models to ones with
species richness and range-size distribution restrictions. Instead, bird
community composition was significantly correlated with elevation and tree
species composition of sites, indicating the influence of deterministic factors
on bird community structure. Conservation of low- and high-elevation areas and
maintenance of tree species composition against habitat alteration are
important for bird conservation in the southern Western Ghats rainforests.Comment: 36 pages, 5 figures, two tables (including one in the appendix)
Submitted to the Journal of the Bombay Natural History Society (JBNHS
Quantum thermodynamics at critical points during melting and solidification processes
We systematically explore and show the existence of finite-temperature
continuous quantum phase transition (CTQPT) at a critical point, namely, during
solidification or melting such that the first-order thermal phase transition is
a special case within CTQPT. Infact, CTQPT is related to chemical reaction
where quantum fluctuation (due to wavefunction transformation) is caused by
thermal energy and it can occur maximally for temperatures much higher than
zero Kelvin. To extract the quantity related to CTQPT, we use the ionization
energy theory and the energy-level spacing renormalization group method to
derive the energy-level spacing entropy, renormalized Bose-Einstein
distribution and the time-dependent specific heat capacity. This work
unambiguously shows that the quantum phase transition applies for any finite
temperatures.Comment: To be published in Indian Journal of Physics (Kolkata
Experimental Methods and Mathematical Models to Examine Durability of Polymer Electrolyte Membrane Fuel Cell Catalysts
Proton exchange membrane fuel cells (PEMFC) are attractive energy sources for power trains in vehicles because of their low operating temperature that enables fast start-up and high power densities. Cost reduction and durability are the key issues to be solved before PEMFCs can be successfully commercialized. The major portion of fuel cell cost is associated with the catalyst layer which is typically comprised of carbon-supported Pt and ionomer. The degradation of the catalyst layer is one of the major failure modes that can cause voltage degradation and limit the service life of the fuel cell stack during operation. To develop a highly durable and better performing catalyst layer, topics such as the causes for the degradation, modes of failure, different mechanisms and effect of degradation on fuel cell performance must be studied thoroughly.
Key degradation modes of catalyst layer are carbon corrosion and Pt dissolution. These two modes change the electrode structure in the membrane electrode assembly (MEA) and result in catalyst layer thinning, CO2 evolution, Pt deposition in the membrane and Pt agglomeration. Alteration of the electrode morphology can lead to voltage degradation.
Accelerated stress tests (ASTs) which simulate the conditions and environments to which fuel cells are subject, but which can be completed in a timely manner, are commonly used to investigate the degradation of the various components. One of the current challenges in employing these ASTs is to relate the performance loss under a given set of conditions to the various life-limiting factors and material changes. In this study, various degradation modes of the cathode catalyst layer are isolated to study their relative impact on performance loss ‗Fingerprints‘ of identifiable performance losses due to carbon corrosion are developed for MEAs with 0.4 mg cm−2 cathode platinum loadings. The fingerprint is used to determine the extent of performance loss due to carbon corrosion and Pt dissolution in cases where both mechanisms operate. This method of deconvoluting the contributions to performance loss is validated by comparison to the measured performance losses when the catalyst layer is subjected to an AST in which Pt dissolution is predominant. The limitations of this method
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are discussed in detail. The developed fingerprint suggests that carbon loss leading to CO2 evolution during carbon corrosion ASTs contributes to performance loss of the cell. A mechanistic model for carbon corrosion of the cathode catalyst layer based on one appearing in the literature is developed and validated by comparison of the predicted carbon losses to those measured during various carbon corrosion ASTs. Practical use of the model is verified by comparing the predicted and experimentally observed performance losses. Analysis of the model reveals that the reversible adsorption of water and subsequent oxidation of the carbon site onto which water is adsorbed is the main cause of the current decay during ASTs.
Operation of PEM fuel cells at higher cell temperatures and lower relative humidities accelerates Pt dissolution in the catalyst layer during ASTs. In this study, the effects of temperature and relative humidity on MEA degradation are investigated by applying a newly developed AST protocol in which Pt dissolution is predominant and involves the application of a potentiostatic square-wave pulse with a repeating pattern of 3s at 0.6 V followed by 3s at 1.0 V. This protocol is applied at three different temperatures (40°C, 60°C and 80°C) to the same MEA. A diagnostic signature is developed to estimate kinetic losses by making use of the effective platinum surface area (EPSA) obtained from cyclic voltammograms. The analysis indicates that performance degradation occurs mainly due to the loss of Pt in electrical contact with the support and becomes particularly large at 80°C.
This Pt dissolution AST protocol is also investigated at three different relative humidities (100%, 50% and 0%). Electrochemical impedance spectroscopy measurements of the MEAs show an increase in both the polarization and ohmic resistances during the course of the AST. Analysis by cyclic voltammetry shows a slight increase in EPSA when the humidity increases from 50% to 100%. The proton resistivity of the ionomer measured by carrying out impedance measurements on MEAs with H2 being fed on the anode side and N2 on the cathode side is found to increase by the time it reaches its end-of-life state when operated under 0 % RH conditions.1 yea
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An Information Modeling Framework for Support of Sustainable Manufacturing System Design Decision Making
Manufacturing technology has continuously evolved and advanced over the past century; this has led to an increase in the production of consumer and industrial goods driven by simultaneous growth in population and wealth. Despite the resulting economic and labor growth, environmental impacts of manufacturing have increased dramatically due to the dependence on exhaustible material and energy resources necessary to meet these growing product demands. Increasing awareness and concern over these impacts has encouraged sustainable thinking toward managing material resources, alternative energy sources, and advanced manufacturing technologies. However, the primary emphasis of manufacturing system design decision making has remained focused on the reduction of cost of goods sold (in discrete part production) and total production cost (in continuous production). Manufacturing system design decision makers face challenges in defining, evaluating, and implementing sustainable manufacturing practices, which include the time-intensive nature of complex system design and analysis, data integrity, and deficiencies in assessment methods. In particular, the challenges of collecting, curating, analyzing, and presenting environmental, economic, and social metrics and indicators (sustainability performance information) remains a barrier to operational decision-making. Existing assessment methods and tools are not well-suited to evaluating the sustainability performance of manufacturing processes and systems, as they tend to be product-focused and have limited ability to adapt to changes at the manufacturing process or system level.
The objective of this dissertation research is to facilitate sustainable manufacturing system design decision making by integrating a systematic and structured information modeling framework with a manufacturing system design approach. To accomplish this goal, the research approach involves four steps: (1) Performing a review of recent literature to identify the existing challenges in the development and application of sustainable manufacturing methods, tool, models, algorithms, metrics, and indicators; (2) Introducing a functional and object-oriented information modeling methodology to characterize the sustainability performance of unit manufacturing processes (UMPs) using the concepts of abstraction and instantiation, which is demonstrated by reusing and extending a manual milling UMP model for two and a half-axis milling process; (3) Applying information modeling approaches in characterizing the sustainability performance of manufacturing process flows composed of UMPs, which is demonstrated for a discrete part manufacturing system; and (4) Synthesizing the results of the prior steps to provide an information modeling framework for sustainable manufacturing system design decision making. The framework is applied to discrete and continuous product manufacturing to demonstrate the flexibility of this system design approach. The framework provides an accessible approach for detailed analysis of the sustainability performance of manufacturing processes and systems by enabling the reuse, extension, and composability of new and previously developed UMP models. The coupling of information modeling concepts (e.g., abstraction, instantiation, and polymorphism) along with hierarchical, structured, and systematic manufacturing system design enables the framework to address the challenges stated above, namely: (1) Modeling complexity is simplified through a bottom-up approach for characterizing individual UMPs, which are built up for system-level characterization; (2) Model development, verification, and validation efforts are reduced by reusing and extending UMP models, thereby also reducing the time-intensity of modeling; (3) Data reliability is improved, since the framework is agnostic of existing process-specific data sources, rather than restricting data sources and types necessary for analysis; and (4) Multi-criteria decision-making is facilitated by using a hierarchical data structure for model-quantified metrics of interest, which supports analysis using decision trees. The research lays a foundation for developing an ontologies based decision support for sustainable manufacturing system design, as ontologies describe relationships and links between systems and sub-systems which enables the framework to have high-fidelity and understanding of the manufacturing system model and data
Diagnosis and Repair for Synthesis from Signal Temporal Logic Specifications
We address the problem of diagnosing and repairing specifications for hybrid
systems formalized in signal temporal logic (STL). Our focus is on the setting
of automatic synthesis of controllers in a model predictive control (MPC)
framework. We build on recent approaches that reduce the controller synthesis
problem to solving one or more mixed integer linear programs (MILPs), where
infeasibility of a MILP usually indicates unrealizability of the controller
synthesis problem. Given an infeasible STL synthesis problem, we present
algorithms that provide feedback on the reasons for unrealizability, and
suggestions for making it realizable. Our algorithms are sound and complete,
i.e., they provide a correct diagnosis, and always terminate with a non-trivial
specification that is feasible using the chosen synthesis method, when such a
solution exists. We demonstrate the effectiveness of our approach on the
synthesis of controllers for various cyber-physical systems, including an
autonomous driving application and an aircraft electric power system
Representation Learning via Manifold Flattening and Reconstruction
This work proposes an algorithm for explicitly constructing a pair of neural
networks that linearize and reconstruct an embedded submanifold, from finite
samples of this manifold. Our such-generated neural networks, called Flattening
Networks (FlatNet), are theoretically interpretable, computationally feasible
at scale, and generalize well to test data, a balance not typically found in
manifold-based learning methods. We present empirical results and comparisons
to other models on synthetic high-dimensional manifold data and 2D image data.
Our code is publicly available.Comment: 44 pages, 19 figure
Defect reduction in a capacitor manufacturing process through Six Sigma concept: A case study
In the present scenario, the Six Sigma tools and techniques are used by various manufacturing industries, exporting industries and even service organizations. It focuses on improving the quality of the products, cutting down the extra costs, reducing the variations and satisfying the customers. This case study follows the Six Sigma tools called DMAIC methodology to identify and analyze various root causes of the capacitors rejection problems, which influence the performance of the company and suggests solutions to counter with it. The issue not only causes financial loss to the company but also hinders future growth in form of customer dissatisfaction. The results of the implementation indicate significant improvement in the quality of the product and cost reduction
Rough Set-hypergraph-based Feature Selection Approach for Intrusion Detection Systems
Immense growth in network-based services had resulted in the upsurge of internet users, security threats and cyber-attacks. Intrusion detection systems (IDSs) have become an essential component of any network architecture, in order to secure an IT infrastructure from the malicious activities of the intruders. An efficient IDS should be able to detect, identify and track the malicious attempts made by the intruders. With many IDSs available in the literature, the most common challenge due to voluminous network traffic patterns is the curse of dimensionality. This scenario emphasizes the importance of feature selection algorithm, which can identify the relevant features and ignore the rest without any information loss. In this paper, a novel rough set κ-Helly property technique (RSKHT) feature selection algorithm had been proposed to identify the key features for network IDSs. Experiments carried using benchmark KDD cup 1999 dataset were found to be promising, when compared with the existing feature selection algorithms with respect to reduct size, classifier’s performance and time complexity. RSKHT was found to be computationally attractive and flexible for massive datasets
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