25 resultados para Alternatives in recession


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Automated synthesis of mechanical designs is an important step towards the development of an intelligent CAD system. Research into methods for supporting conceptual design using automated synthesis has attracted much attention in the past decades. In our research, ten experimental studies are conducted to find out how designers synthesize solution concepts for multi-state mechanical devices. The designers are asked to think aloud, while carrying out the synthesis. These design synthesis processes are video recorded. It has been found that modification of kinematic pairs and mechanisms is the major activity carried out by all the designers. This paper presents an analysis of these synthesis processes using configuration space and topology graph to identify and classify the types of modifications that take place. Understanding of these modification processes and the context in which they happened is crucial to develop a system for supporting design synthesis of multiple state mechanical devices that is capable of creating a comprehensive variety of solution alternatives.

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We consider the Randall-Sundrum (RS) setup to be a theory of flavor, as an alternative to Froggatt-Nielsen models instead of as a solution to the hierarchy problem. The RS framework is modified by taking the low-energy brane to be at the grand unified theory (GUT) scale. This also alleviates constraints from flavor physics. Fermion masses and mixing angles are fit at the GUT scale. The ranges of the bulk mass parameters are determined using a chi(2) fit taking into consideration the variation in O(1) parameters. In the hadronic sector, the heavy top quark requires large bulk mass parameters localizing the right-handed top quark close to the IR brane. Two cases of neutrino masses are considered: (a) Planck scale lepton number violation and (b) Dirac neutrino masses. Contrary to the case of weak scale RS models, both these cases give reasonable fits to the data, with the Planck scale lepton number violation fitting slightly better compared to the Dirac case. In the supersymmetric version, the fits are not significantly different except for the variation in tan beta. If the Higgs superfields and the supersymmetry breaking spurion are localized on the same brane, then the structure of the sfermion masses are determined by the profiles of the zero modes of the hypermultiplets in the bulk. Trilinear terms have the same structure as the Yukawa matrices. The resultant squark spectrum is around similar to 2-3 TeV required by the light Higgs mass to be around 125 GeV and to satisfy the flavor violating constraints.

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Algae biofuel have emerged as viable renewable energy sources and are the potential alternatives to fossil-based fuels in recent times. Algae have the potential to generate significant quantities of commercially viable biofuel apart from treating wastewater. Three algal species, viz. Chlorococcum sp., Microcystis sp. and Phormidium sp. proliferating in wastewater ponds were isolated and cultured in the laboratory myxotrophically under similar wastewater conditions. Chlorococcum sp. attained a mean biomass productivity of 0.09 g. I(-1)d(-1) with the maximum `biomass density of 1.33 g I-1 and comparatively higher lipid content of 30.55% (w/w) on the ninth day of the culture experiment. Under similar conditions Microcystis sp. and Phormidium sp. attained mean biomass productivities of 0.058 and 0.063 g I-1 d(-1) with a total lipid content of 8.88% and 18.66% respectively. Biochemical composition (carbohydrates, proteins, lipids and phosphates) variations and lipid accumulation studies were performed by comparison of the ratios of carbohydrate to protein; lipid to protein (L/P) and lipid to phosphates using attenuated total reflectance-Fourier transform infrared spectroscopy which showed higher L/P ratio during the stationary phase of algal growth. Composition analysis of fatty acid methyl ester has been performed using gas chromatography and mass spectrometry. Chlorococcum sp. with higher productivity and faster growth rate has higher lipid content with about 67% of saturated fatty acid dominated by palmitate (36.3%) followed by an unsaturate as linoleate (14%) and has proved to be an economical and viable feedstock for biofuel production compared to the other wastewater-grown species.

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In social choice theory, preference aggregation refers to computing an aggregate preference over a set of alternatives given individual preferences of all the agents. In real-world scenarios, it may not be feasible to gather preferences from all the agents. Moreover, determining the aggregate preference is computationally intensive. In this paper, we show that the aggregate preference of the agents in a social network can be computed efficiently and with sufficient accuracy using preferences elicited from a small subset of critical nodes in the network. Our methodology uses a model developed based on real-world data obtained using a survey on human subjects, and exploits network structure and homophily of relationships. Our approach guarantees good performance for aggregation rules that satisfy a property which we call expected weak insensitivity. We demonstrate empirically that many practically relevant aggregation rules satisfy this property. We also show that two natural objective functions in this context satisfy certain properties, which makes our methodology attractive for scalable preference aggregation over large scale social networks. We conclude that our approach is superior to random polling while aggregating preferences related to individualistic metrics, whereas random polling is acceptable in the case of social metrics.

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Recession flows in a basin are controlled by the temporal evolution of its active drainage network (ADN). The geomorphological recession flow model (GRFM) assumes that both the rate of flow generation per unit ADN length (q) and the speed at which ADN heads move downstream (c) remain constant during a recession event. Thereby, it connects the power law exponent of -dQ/dt versus Q (discharge at the outlet at time t) curve, , with the structure of the drainage network, a fixed entity. In this study, we first reformulate the GRFM for Horton-Strahler networks and show that the geomorphic ((g)) is equal to D/(D-1), where D is the fractal dimension of the drainage network. We then propose a more general recession flow model by expressing both q and c as functions of Horton-Strahler stream order. We show that it is possible to have = (g) for a recession event even when q and c do not remain constant. The modified GRFM suggests that is controlled by the spatial distribution of subsurface storage within the basin. By analyzing streamflow data from 39 U.S. Geological Survey basins, we show that is having a power law relationship with recession curve peak, which indicates that the spatial distribution of subsurface storage varies across recession events. Key Points The GRFM is reformulated for Horton-Strahler networks. The GRFM is modified by allowing its parameters to vary along streams. Sub-surface storage distribution controls recession flow characteristics.

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Since Brutsaert and Neiber (1977), recession curves are widely used to analyse subsurface systems of river basins by expressing -dQ/dt as a function of Q, which typically take a power law form: -dQ/dt=kQ, where Q is the discharge at a basin outlet at time t. Traditionally recession flows are modelled by single reservoir models that assume a unique relationship between -dQ/dt and Q for a basin. However, recent observations indicate that -dQ/dt-Q relationship of a basin varies greatly across recession events, indicating the limitation of such models. In this study, the dynamic relationship between -dQ/dt and Q of a basin is investigated through the geomorphological recession flow model which models recession flows by considering the temporal evolution of its active drainage network (the part of the stream network of the basin draining water at time t). Two primary factors responsible for the dynamic relationship are identified: (i) degree of aquifer recharge (ii) spatial variation of rainfall. Degree of aquifer recharge, which is likely to be controlled by (effective) rainfall patterns, influences the power law coefficient, k. It is found that k has correlation with past average streamflow, which confirms the notion that dynamic -dQ/dt-Q relationship is caused by the degree of aquifer recharge. Spatial variation of rainfall is found to have control on both the exponent, , and the power law coefficient, k. It is noticed that that even with same and k, recession curves can be different, possibly due to their different (recession) peak values. This may also happen due to spatial variation of rainfall. Copyright (c) 2012 John Wiley & Sons, Ltd.

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The study of recession flows offers fundamental insights into basin hydrological processes and, in particular, into the collective behavior of the governing dominant subsurface flows and properties. We use here an existing geomorphological interpretation of recession dynamics, which links the exponent in the classic recession curve -dQ/dt - kQ(alpha) to the geometric properties of the time-varying drainage network to study the general properties of recession curves across a wide variety of river basins. In particular, we show how the parameter k depends on the initial soil moisture state of the basin and can be made to explicitly depend on an index discharge, representative of initial sub-subsurface storage. Through this framework we obtain a non-dimensional, event-independent, recession curve. We subsequently quantify the variability of k across different basins on the basis of their geometry, and, by rescaling, collapse curves from different events and basins to obtain a generalized, or `universal', recession curve. Finally, we analyze the resulting normalized recession curves and explain their universal characteristics, lending further support to the notion that the statistical properties of observed recession curves bear the signature of the geomorphological structure of the networks producing them. (C) 2014 Elsevier Ltd. All rights reserved.

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The drying of sessile, nano-silica laden water droplet is studied under ambient conditions, in the absence of any convection. The drying process can be divided into two distinct regimes. During regime 1, the outer edge of the droplet remains pinned and particles agglomerate at the droplet periphery similar to the traditional coffee ring. However in regime 2, with further evaporation, both the liquid contact line and the agglomeration front starts moving radially inwards from the initial contact edge. The contact between the liquid and the agglomerate is maintained throughout regime 2 and the vaporisation driven liquid edge recession essentially drives the inward growth of the particle deposition. Fast kinetics of particle aggregation results in rapid growth of this agglomeration front as seen from the experiments. A theoretical formulation involving a simplistic model of the agglomeration front growth based on particle mass balance has been proposed. (C) 2014 Elsevier Ltd. All rights reserved,

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This study concerns the relationship between the power law recession coefficient k (in - dQ/dt = kQ(alpha), Q being discharge at the basin outlet) and past average discharge Q(N) (where N is the temporal distance from the center of the selected time span in the past to the recession peak), which serves as a proxy for past storage state of the basin. The strength of the k-Q(N) relationship is characterized by the coefficient of determination R-N(2), which is expected to indicate the basin's ability to hold water for N days. The main objective of this study is to examine how R-N(2) value of a basin is related with its physical characteristics. For this purpose, we use streamflow data from 358 basins in the United States and selected 18 physical parameters for each basin. First, we transform the physical parameters into mutually independent principal components. Then we employ multiple linear regression method to construct a model of R-N(2) in terms of the principal components. Furthermore, we employ step-wise multiple linear regression method to identify the dominant catchment characteristics that influence R-N(2) and their directions of influence. Our results indicate that R-N(2) is appreciably related to catchment characteristics. Particularly, it is noteworthy that the coefficient of determination of the relationship between R-N(2) and the catchment characteristics is 0.643 for N = 45. We found that topographical characteristics of a basin are the most dominant factors in controlling the value of R-N(2). Our results may be suggesting that it is possible to tell about the water holding capacity of a basin by just knowing about a few of its physical characteristics. (C) 2015 Elsevier B.V. All rights reserved.