973 resultados para LINEAR-CHAIN


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Franchising has become a way to minimise the risks of small business management. There has been little research into the factors that promote franchise relationship success. This study attempts to empirically examine the important elements (relationship quality, customer loyalty and cooperation), which might promote a successful long-term franchising relationship between franchisors and franchisees within the context of convenience stores in Taiwan. A model of these relationships was developed and tested. A total of 500 surveys were mailed to a random sample of convenience stores’ franchisee owners among the four main franchisors in Taiwan. The results show that relationship quality positively influences the cooperation between franchisors and franchisees and is positively correlated with franchisee loyalty. Additionally, the cooperative behaviour between franchisees and franchisors is significantly associated with franchisees’ loyalty.

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Learning and memory depend on signaling mole- cules that affect synaptic efficacy. The cytoskeleton has been implicated in regulating synaptic transmission but its role in learning and memory is poorly understood. Fear learning depends on plasticity in the lateral nucleus of the amygdala. We therefore examined whether the cytoskeletal-regulatory protein, myosin light chain kinase, might contribute to fear learning in the rat lateral amygdala. Microinjection of ML-7, a specific inhibitor of myosin light chain kinase, into the lateral nucleus of the amygdala before fear conditioning, but not immediately afterward, enhanced both short-term memory and long-term memory, suggesting that myosin light chain kinase is involved specifically in memory acquisition rather than in posttraining consolidation of memory. Myosin light chain kinase inhibitor had no effect on memory retrieval. Furthermore, ML-7 had no effect on behavior when the train- ing stimuli were presented in a non-associative manner. An- atomical studies showed that myosin light chain kinase is present in cells throughout lateral nucleus of the amygdala and is localized to dendritic shafts and spines that are postsynaptic to the projections from the auditory thalamus to lateral nucleus of the amygdala, a pathway specifically impli- cated in fear learning. Inhibition of myosin light chain kinase enhanced long-term potentiation, a physiological model of learning, in the auditory thalamic pathway to the lateral nu- cleus of the amygdala. When ML-7 was applied without as- sociative tetanic stimulation it had no effect on synaptic responses in lateral nucleus of the amygdala. Thus, myosin light chain kinase activity in lateral nucleus of the amygdala appears to normally suppress synaptic plasticity in the cir- cuits underlying fear learning, suggesting that myosin light chain kinase may help prevent the acquisition of irrelevant fears. Impairment of this mechanism could contribute to pathological fear learning.

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Diabetic peripheral neuropathy (DPN) is one of the most common long-term complications of diabetes. The accurate detection and quantification of DPN are important for defining at-risk patients, anticipating deterioration, and assessing new therapies. Current methods of detecting and quantifying DPN, such as neurophysiology, lack sensitivity, require expert assessment and focus primarily on large nerve fibers. However, the earliest damage to nerve fibers in diabetic neuropathy is to the small nerve fibers. At present, small nerve fiber damage is currently assessed using skin/nerve biopsy; both are invasive technique and are not suitable for repeated investigations.

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Visual localization in outdoor environments is often hampered by the natural variation in appearance caused by such things as weather phenomena, diurnal fluctuations in lighting, and seasonal changes. Such changes are global across an environment and, in the case of global light changes and seasonal variation, the change in appearance occurs in a regular, cyclic manner. Visual localization could be greatly improved if it were possible to predict the appearance of a particular location at a particular time, based on the appearance of the location in the past and knowledge of the nature of appearance change over time. In this paper, we investigate whether global appearance changes in an environment can be learned sufficiently to improve visual localization performance. We use time of day as a test case, and generate transformations between morning and afternoon using sample images from a training set. We demonstrate the learned transformation can be generalized from training data and show the resulting visual localization on a test set is improved relative to raw image comparison. The improvement in localization remains when the area is revisited several weeks later.

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This article investigates the extent to which the purported greening of food retailing and consumption in Australia is consistent with the development of a corporate-environmental food regime. Recent developments in food regime theory, particularly the concept of an emerging third food regime (the so-called ‘corporate-environmental food regime’), provide a useful organizing framework for understanding recent agri-restructuring trends. We find that, while a globally based, third food regime is becoming more apparent, the attributes that relate to corporate retail-driven greening of the supply chain are less evident within Australia’s domestic market than in its EU counterparts. However, there is some evidence that Australia’s export market is subject to some degree of ‘greening at a distance’ due to private regulations imposed by supermarkets overseas. We argue that while broader agri-restructuring trends may be evident at an international level, elements of greening specific to national contexts are important for determining the trajectory of any third food regime.

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UV-vis photodissociation action spectroscopy is becoming increasingly prevalent because of advances in, and commercial availability of, ion trapping technologies and tunable laser sources. This study outlines in detail an instrumental arrangement, combining a commercial ion-trap mass spectrometer and tunable nanosecond pulsed laser source, for performing fully automated photodissociation action spectroscopy on gas-phase ions. The components of the instrumentation are outlined, including the optical and electronic interfacing, in addition to the control software for automating the experiment and performing online analysis of the spectra. To demonstrate the utility of this ensemble, the photodissociation action spectra of 4-chloroanilinium, 4-bromoanilinium, and 4-iodoanilinium cations are presented and discussed. Multiple photoproducts are detected in each case and the photoproduct yields are followed as a function of laser wavelength. It is shown that the wavelength-dependent partitioning of the halide loss, H loss, and NH3 loss channels can be broadly rationalized in terms of the relative carbon-halide bond dissociation energies and processes of energy redistribution. The photodissociation action spectrum of (phenyl)Ag-2 (+) is compared with a literature spectrum as a further benchmark.

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RATIONALE Both traditional electron ionization and electrospray ionization tandem mass spectrometry have demonstrated limitations in the unambiguous identification of fatty acids. In the former case, high electron energies lead to extensive dissociation of the radical cations from which little specific structural information can be obtained. In the latter, conventional collision-induced dissociation (CID) of even-electron ions provides little intra-chain fragmentation and thus few structural diagnostics. New approaches that harness the desirable features of both methods, namely radical-driven dissociation with discrete energy deposition, are thus required. METHODS Herein we describe the derivatization of a structurally diverse suite of fatty acids as 4-iodobenzyl esters (FAIBE). Electrospray ionization of these derivatives in the presence of sodium acetate yields abundant [M+Na]+ ions that can be mass-selected and subjected to laser irradiation (=266nm) on a modified linear ion-trap mass spectrometer. RESULTS Photodissociation (PD) of the FAIBE derivatives yields abundant radical cations by loss of atomic iodine and in several cases selective dissociation of activated carboncarbon bonds (e.g., at allylic positions) are also observed. Subsequent CID of the [M+NaI]center dot+ radical cations yields radical-directed dissociation (RDD) mass spectra that reveal extensive carboncarbon bond dissociation without scrambling of molecular information. CONCLUSIONS Both PD and RDD spectra obtained from derivatized fatty acids provide a wealth of structural information including the position(s) of unsaturation, chain-branching and hydroxylation. The structural information obtained by this approach, in particular the ability to rapidly differentiate isomeric lipids, represents a useful addition to the lipidomics tool box. Copyright (c) 2013 John Wiley & Sons, Ltd.

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Standard Monte Carlo (sMC) simulation models have been widely used in AEC industry research to address system uncertainties. Although the benefits of probabilistic simulation analyses over deterministic methods are well documented, the sMC simulation technique is quite sensitive to the probability distributions of the input variables. This phenomenon becomes highly pronounced when the region of interest within the joint probability distribution (a function of the input variables) is small. In such cases, the standard Monte Carlo approach is often impractical from a computational standpoint. In this paper, a comparative analysis of standard Monte Carlo simulation to Markov Chain Monte Carlo with subset simulation (MCMC/ss) is presented. The MCMC/ss technique constitutes a more complex simulation method (relative to sMC), wherein a structured sampling algorithm is employed in place of completely randomized sampling. Consequently, gains in computational efficiency can be made. The two simulation methods are compared via theoretical case studies.

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Contemporary lipidomics protocols are dependent on conventional tandem mass spectrometry for lipid identification. This approach is extremely powerful for determining lipid class and identifying the number of carbons and the degree of unsaturation of any acyl-chain substituents. Such analyses are however, blind to isomeric variants arising from different carbon carbon bonding motifs within these chains including double bond position, chain branching, and cyclic structures. This limitation arises from the fact that conventional, low energy collision-induced dissociation of even-electron lipid ions does not give rise to product ions from intrachain fragmentation of the fatty acyl moieties. To overcome this limitation, we have applied radical-directed dissociation (RDD) to the study of lipids for the first time. In this approach, bifunctional molecules that contain a photocaged radical initiator and a lipid-adducting group, such as 4-iodoaniline and 4-iodobenzoic acid, are used to form noncovalent complexes (i.e., adduct ions) with a lipid during electrospray ionization. Laser irradiation of these complexes at UV wavelengths (266 nm) cleaves the carbon iodine bond to liberate a highly reactive phenyl radical. Subsequent activation of the nascent radical ions results in RDD with significant intrachain fragmentation of acyl moieties. This approach provides diagnostic fragments that are associated with the double bond position and the positions of chain branching in glycerophospholipids, sphingomyelins and triacylglycerols and thus can be used to differentiate isomeric lipids differing only in such motifs. RDD is demonstrated for well-defined lipid standards and also reveals lipid structural diversity in olive oil and human very-low density lipoprotein.

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The present article gives an overview of the reversible addition fragmentation chain transfer (RAFT) process. RAFT is one of the most versatile living radical polymerization systems and yields polymers of predictable chain length and narrow molecular weight distribution. RAFT relies on the rapid exchange of thiocarbonyl thio groups between growing polymeric chains. The key strengths of the RAFT process for polymer design are its high tolerance of monomer functionality and reaction conditions, the wide range of well-controlled polymeric architectures achievable, and its (in-principle) non-rate-retarding nature. This article introduces the mechanism of polymerization, the range of polymer molecular weights achievable, the range of monomers in which polymerization is controlled by RAFT, the various polymeric architectures that can be obtained, the type of end-group functionalities available to RAFT-made polymers, and the process of RAFT polymerization.

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Molecular orbital calculations have predicted the stability of a range of connectivities for the radical C5H potential surface. The most energetically favorable of these include the linear C4CH geometry and two ring-chain structures HC2C3 and C2C3H The corresponding anions are also shown to be theoretically stable, and furthermore, a fourth isomer, C2CHC2, is predicted to be the most stable anion connectivity. These results have motivated experimental efforts. Methodologies for the generation of the non-ring-containing isomeric anions C4CH and C2CHC2 have been developed utilizing negative ion mass spectrometry. The absolute connectivities of the anions have been established using deuterium labeling, charge reversal, and neutralization reionization techniques. The success of the latter experiment confirms theoretical predictions of stability of the corresponding neutral species. This is the first reported observation of the neutral C2CHC2 species that calculations predict to be substantially less stable than the C4CH connectivity but still bound relative to isomerization processes.

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The exchange of physical forces in both cell-cell and cell-matrix interactions play a significant role in a variety of physiological and pathological processes, such as cell migration, cancer metastasis, inflammation and wound healing. Therefore, great interest exists in accurately quantifying the forces that cells exert on their substrate during migration. Traction Force Microscopy (TFM) is the most widely used method for measuring cell traction forces. Several mathematical techniques have been developed to estimate forces from TFM experiments. However, certain simplifications are commonly assumed, such as linear elasticity of the materials and/or free geometries, which in some cases may lead to inaccurate results. Here, cellular forces are numerically estimated by solving a minimization problem that combines multiple non-linear FEM solutions. Our simulations, free from constraints on the geometrical and the mechanical conditions, show that forces are predicted with higher accuracy than when using the standard approaches.

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We address the problem of finite horizon optimal control of discrete-time linear systems with input constraints and uncertainty. The uncertainty for the problem analysed is related to incomplete state information (output feedback) and stochastic disturbances. We analyse the complexities associated with finding optimal solutions. We also consider two suboptimal strategies that could be employed for larger optimization horizons.

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In the finite element modelling of steel frames, external loads usually act along the members rather than at the nodes only. Conventionally, when a member is subjected to these transverse loads, they are converted to nodal forces which act at the ends of the elements into which the member is discretised by either lumping or consistent nodal load approaches. For a contemporary geometrically non-linear analysis in which the axial force in the member is large, accurate solutions are achieved by discretising the member into many elements, which can produce unfavourable consequences on the efficacy of the method for analysing large steel frames. Herein, a numerical technique to include the transverse loading in the non-linear stiffness formulation for a single element is proposed, and which is able to predict the structural responses of steel frames involving the effects of first-order member loads as well as the second-order coupling effect between the transverse load and the axial force in the member. This allows for a minimal discretisation of a frame for second-order analysis. For those conventional analyses which do include transverse member loading, prescribed stiffness matrices must be used for the plethora of specific loading patterns encountered. This paper shows, however, that the principle of superposition can be applied to the equilibrium condition, so that the form of the stiffness matrix remains unchanged with only the magnitude of the loading being needed to be changed in the stiffness formulation. This novelty allows for a very useful generalised stiffness formulation for a single higher-order element with arbitrary transverse loading patterns to be formulated. The results are verified using analytical stability function studies, as well as with numerical results reported by independent researchers on several simple structural frames.

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When radiation therapy centres are equipped with two or more linear accelerators from the same vendor, they are usually beam-matched. This work tested the sensitivity of optically stimulated luminescence dosimeters (OSLDs) across matched linear accelerators. The responses were compared with an unshielded diode detector for varying field sizes. Clinical studies are currently done with thermoluminescent dosimeters (TLD), which absorb radiation then emit some levels of light determined by the radiation absorption when heated.