983 resultados para Nonprofit industrial complex
Resumo:
Three-dimensional (3-D) kinematical conservation laws (KCL) are equations of evolution of a propagating surface Omega(t) in three space dimensions. We start with a brief review of the 3-D KCL system and mention some of its properties relevant to this paper. The 3-D KCL, a system of six conservation laws, is an underdetermined system to which we add an energy transport equation for a small amplitude 3-D nonlinear wavefront propagating in a polytropic gas in a uniform state and at rest. We call the enlarged system of 3-D KCL with the energy transport equation equations of weakly nonlinear ray theory (WNLRT). We highlight some interesting properties of the eigenstructure of the equations of WNLRT, but the main aim of this paper is to test the numerical efficacy of this system of seven conservation laws. We take several initial shapes for a nonlinear wavefront with a suitable amplitude distribution on it and let it evolve according to the 3-D WNLRT. The 3-D WNLRT is a weakly hyperbolic 7 x 7 system that is highly nonlinear. Here we use the staggered Lax-Friedrichs and Nessyahu-Tadmor central schemes and have obtained some very interesting shapes of the wavefronts. We find the 3-D KCL to be suitable for solving many complex problems for which there presently seems to be no other method capable of giving such physically realistic features.
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Processes in complex chemical systems, such as macromolecules, electrolytes, interfaces, micelles and enzymes, can span several orders of magnitude in length and time scales. The length and time scales of processes occurring over this broad time and space window are frequently coupled to give rise to the control necessary to ensure specificity and the uniqueness of the chemical phenomena. A combination of experimental, theoretical and computational techniques that can address a multiplicity of length and time scales is required in order to understand and predict structure and dynamics in such complex systems. This review highlights recent experimental developments that allow one to probe structure and dynamics at increasingly smaller length and time scales. The key theoretical approaches and computational strategies for integrating information across time-scales are discussed. The application of these ideas to understand phenomena in various areas, ranging from materials science to biology, is illustrated in the context of current developments in the areas of liquids and solvation, protein folding and aggregation and phase transitions, nucleation and self-assembly.
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This master thesis studies how trade liberalization affects the firm-level productivity and industrial evolution. To do so, I built a dynamic model that considers firm-level productivity as endogenous to investigate the influence of trade on firm’s productivity and the market structure. In the framework, heterogeneous firms in the same industry operate differently in equilibrium. Specifically, firms are ex ante identical but heterogeneity arises as an equilibrium outcome. Under the setting of monopolistic competition, this type of model yields an industry that is represented not by a steady-state outcome, but by an evolution that rely on the decisions made by individual firms. I prove that trade liberalization has a general positive impact on technological adoption rates and hence increases the firm-level productivity. Besides, this endogenous technology adoption model also captures the stylized facts: exporting firms are larger and more productive than their non-exporting counterparts in the same sector. I assume that the number of firms is endogenous, since, according to the empirical literature, the industrial evolution shows considerably different patterns across countries; some industries experience large scale of firms’ exit in the period of contracting market shares, while some industries display relative stable number of firms or gradually increase quantities. The special word “shakeout” is used to describe the dramatic decrease in the number of firms. In order to explain the causes of shakeout, I construct a model where forward-looking firms decide to enter and exit the market on the basis of their state of technology. In equilibrium, firms choose different dates to adopt innovation which generate a gradual diffusion process. It is exactly this gradual diffusion process that generates the rapid, large-scale exit phenomenon. Specifically, it demonstrates that there is a positive feedback between firm’s exit and adoption, the reduction in the number of firms increases the incentives for remaining firms to adopt innovation. Therefore, in the setting of complete information, this model not only generates a shakeout but also captures the stability of an industry. However, the solely national view of industrial evolution neglects the importance of international trade in determining the shape of market structure. In particular, I show that the higher trade barriers lead to more fragile markets, encouraging the over-entry in the initial stage of industry life cycle and raising the probability of a shakeout. Therefore, more liberalized trade generates more stable market structure from both national and international viewpoints. The main references are Ederington and McCalman(2008,2009).
Resumo:
Analysis of EXAFS data of complex systems containing more than one phase and one type of coordination, has been discussed. It is shown that a modified treatment of EXAFS function as well as the amplitude ratio plots provide useful means of obtaining valuable structural information. The systems investigated are: biphasic Ni+NiO mixture, NiAl2O4 with two coordinations for Ni, NiO+NiAl2O4 mixture, CoS+CoO system and Ni dispersed on Al2O3. The results obtained with these systems have been most satisfactory and serve to illustrate the utility and the applicability of the innovations described in this paper.
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Multilevel converters have been under research and development for more than three decades and have found successful industrial application. However, this is still a technology under development, and many new contributions and new commercial topologies have been reported in the last few years. The aim of this paper is to group and review these recent contributions, in order to establish the current state of the art and trends of the technology, to provide readers with a comprehensive and insightful review of where multilevel converter technology stands and is heading. This paper first presents a brief overview of well-established multilevel converters strongly oriented to their current state in industrial applications to then center the discussion on the new converters that have made their way into the industry. In addition, new promising topologies are discussed. Recent advances made in modulation and control of multilevel converters are also addressed. A great part of this paper is devoted to show nontraditional applications powered by multilevel converters and how multilevel converters are becoming an enabling technology in many industrial sectors. Finally, some future trends and challenges in the further development of this technology are discussed to motivate future contributions that address open problems and explore new possibilities.
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Several lines of evidence suggest that cancer progression is associated with up-regulation or reactivation of telomerase and the underlying mechanism remains an active area of research. The heterotrimeric MRN complex, consisting of Mre11, Rad50 and Nbs1, which is required for the repair of double-strand breaks, plays a key role in telomere length maintenance. In this study, we show significant differences in the levels of expression of MRN complex subunits among various cancer cells and somatic cells. Notably, siRNA-mediated depletion of any of the subunits of MRN complex led to complete ablation of other subunits of the complex. Treatment of leukemia and prostate cancer cells with etoposide lead to increased expression of MRN complex subunits, with concomitant decrease in the levels of telomerase activity, compared to breast cancer cells. These studies raise the possibility of developing anti-cancer drugs targeting MRN complex subunits to sensitize a subset of cancer cells to radio- and/or chemotherapy. (C) 2010 Elsevier Inc. All rights reserved.
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The copper complex of the antituberculous drug, isonicotinic acid hydrazide (INH), inhibits the RNA-dependent DNA polymerase of Rous sarcoma virus and inactivates its ability to malignantly transform chick embryo cells. The INH-copper complex binds to the 70S genome RNA of Rous sarcoma virus (RSV), which may account for its ability to inhibit the RNA-dependent DNA polymerase. The complex binds RNA more effectively than DNA in contrast to M-IBT-copper complexes, which bind both types of nucleic acids equally. The homopolymers, poly rA and poly rU, are bound by the INH-copper complex to a greater extent than poly rC. Isonicotinic acid hydrazide alone and CuSO4 alone bind neither DNA, RNA, poly (rA), poly (rU), nor poly (rC). However, CuSO4 alone binds poly (rI); INH alone does not. In addition to viral DNA synthesis, chick-embryo cell DNA synthesis is inhibited by the INH-copper complex. The extent of inhibition of cellular DNA synthesis is greater than that of cellular RNA and protein synthesis. No selective inhibition of transformation in cells previously infected with Rous sarcoma virus is observed.
Resumo:
The electrochemical reduction of Cu(II)-CyDTA (CyDTA — trans 1,2-cyclohexanediamine N, N, N′, N′ tetraacetic acid) by impedance method reveals the unusual behaviour of complex plane polarograms owing to potential dependence of double layer capacitance. The impedance plane plots by frequency variation method indicates the quasi-reversible nature of the system. From these plots the chargetransfer resistance at various potentials was evaluated. The standard rate constant was evaluated which complements the prediction of impedance plots for the quasireversible behaviour of the system.
Resumo:
The study of electrochemical reduction of Cu(II)-EDTA system by phase sensitive a.c. impedance method at dropping mercury electrode reveals several interesting features. The complex plane polarograms exhibit loop like shape in contrast to the classical zinc ion reduction where crest like shape is found. Again, the relative placement of peaks of in-phase and quadrature components, and the relative placement of portions before and after the peaks of complex plane polarograms are different from that of zinc ion reduction. The complex plane plots suggest that electrochemical reduction of Cu-EDTA is charge transfer controlled.
Resumo:
Promethazine picrate (C23H23N5O7S) crystallises in the triclinic space group P[unk] with a = 8.137(1), b = 8.144(3), c = 19.224(6) Å, α = 87.78(3), β = 79.97(2), γ = 70.57(2)° and two molecules per unit cell. The structure was solved by direct methods (MULTAN 80) using 2438 observed reflections [I > 2.5 σ(I)]. Refinement was carried out by block-diagonal least-squares methods to a final R = 0.052. The picrate group is planar and is almost perpendicular to the promethazine plane. The two groups are joined by a hydrogen bond. The pairs of molecules related by a centre of symmetry make a molecular arrangement where promethazine and picrate groups are packed in sheets in three dimensions.
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In the study, the potential allowable cut in the district of Pohjois-Savo - based on the non-industrial private forest landowners' (NIPF) choices of timber management strategies - was clarified. Alternative timber management strategies were generated, and the choices and factors affecting the choices of timber management strategies by NIPF landowners were studied. The choices of timber management strategies were solved by maximizing the utility functions of the NIPF landowners. The parameters of the utility functions were estimated using the Analytic Hierarchy Process (AHP). The level of the potential allowable cut was compared to the cutting budgets based on the 7th and 8th National Forest Inventories (NFI7 and NFI8), to the combining of private forestry plans, and to the realized drain from non-industrial private forests. The potential allowable cut was calculated using the same MELA system as has been used in the calculation of the national cutting budget. The data consisted of the NIPF holdings (from the TASO planning system) that had been inventoried compartmentwise and had forestry plans made during the years 1984-1992. The NIPF landowners' choices of timber management strategies were clarified by a two-phase mail inquiry. The most preferred strategy obtained was "sustainability" (chosen by 62 % of landowners). The second in order of preference was "finance" (17 %) and the third was "saving" (11 %). "No cuttings", and "maximum cuttings" were the least preferred (9 % and 1 %, resp.). The factors promoting the choices of strategies with intensive cuttings were a) "farmer as forest owner" and "owning fields", b) "increase in the size of the forest holding", c) agriculture and forestry orientation in production, d) "decreasing short term stumpage earning expectations", e) "increasing intensity of future cuttings", and f) "choice of forest taxation system based on site productivity". The potential allowable cut defined in the study was 20 % higher than the average of the realized drain during the years 1988-1993, which in turn, was at the same level as the cutting budget based on the combining of forestry plans in eastern Finland. Respectively, the potential allowable cut defined in the study was 12 % lower than the NFI8-based greatest sustained allowable cut for the 1990s. Using the method presented in this study, timber management strategies can be clarified for non-industrial private forest landowners in different parts of Finland. Based on the choices of timber managemet strategies, regular cutting budgets can be calculated more realistically than before.
Resumo:
The factors affecting the non-industrial, private forest landowners' (hereafter referred to using the acronym NIPF) strategic decisions in management planning are studied. A genetic algorithm is used to induce a set of rules predicting potential cut of the landowners' choices of preferred timber management strategies. The rules are based on variables describing the characteristics of the landowners and their forest holdings. The predictive ability of a genetic algorithm is compared to linear regression analysis using identical data sets. The data are cross-validated seven times applying both genetic algorithm and regression analyses in order to examine the data-sensitivity and robustness of the generated models. The optimal rule set derived from genetic algorithm analyses included the following variables: mean initial volume, landowner's positive price expectations for the next eight years, landowner being classified as farmer, and preference for the recreational use of forest property. When tested with previously unseen test data, the optimal rule set resulted in a relative root mean square error of 0.40. In the regression analyses, the optimal regression equation consisted of the following variables: mean initial volume, proportion of forestry income, intention to cut extensively in future, and positive price expectations for the next two years. The R2 of the optimal regression equation was 0.34 and the relative root mean square error obtained from the test data was 0.38. In both models, mean initial volume and positive stumpage price expectations were entered as significant predictors of potential cut of preferred timber management strategy. When tested with the complete data set of 201 observations, both the optimal rule set and the optimal regression model achieved the same level of accuracy.
Resumo:
The methods of secondary wood processing are assumed to evolve over time and to affect the requirements set for the wood material and its suppliers. The study aimed at analysing the industrial operating modes applied by joinery and furniture manufacturers as sawnwood users. Industrial operating mode was defined as a pattern of important decisions and actions taken by a company which describes the company's level of adjustment in the late-industrial transition. A non-probabilistic sample of 127 companies was interviewed, including companies from Denmark, Germany, the Netherlands, and Finland. Fifty-two of the firms were furniture manufacturers and the other 75 were producing windows and doors. Variables related to business philosophy, production operations, and supplier choice criteria were measured and used as a basis for a customer typology; variables related to wood usage and perceived sawmill performance were measured to be used to profile the customer types. Factor analysis was used to determine the latent dimensions of industrial operating mode. Canonical correlations analysis was applied in developing the final base for classifying the observations. Non-hierarchical cluster analysis was employed to build a five-group typology of secondary wood processing firms; these ranged from traditional mass producers to late-industrial flexible manufacturers. There is a clear connection between the amount of late-industrial elements in a company and the share of special and customised sawnwood it uses. Those joinery or furniture manufacturers that are more late-industrial also are likely to use more component-type wood material and to appreciate customer-oriented technical precision. The results show that the change is towards the use of late-industrial sawnwood materials and late-industrial supplier relationships.