995 resultados para Extensive conditions


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We have been able to convert a small α/β protein, acylphosphatase, from its soluble and native form into insoluble amyloid fibrils of the type observed in a range of pathological conditions. This was achieved by allowing slow growth in a solution containing moderate concentrations of trifluoroethanol. When analyzed with electron microscopy, the protein aggregate present in the sample after long incubation times consisted of extended, unbranched filaments of 30–50 Å in width that assemble subsequently into higher order structures. This fibrillar material possesses extensive β-sheet structure as revealed by far-UV CD and IR spectroscopy. Furthermore, the fibrils exhibit Congo red birefringence, increased fluorescence with thioflavine T and cause a red-shift of the Congo red absorption spectrum. All of these characteristics are typical of amyloid fibrils. The results indicate that formation of amyloid occurs when the native fold of a protein is destabilized under conditions in which noncovalent interactions, and in particular hydrogen bonding, within the polypeptide chain remain favorable. We suggest that amyloid formation is not restricted to a small number of protein sequences but is a property common to many, if not all, natural polypeptide chains under appropriate conditions.

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The hydrolysis of cell wall pectins by tomato (Lycopersicon esculentum) polygalacturonase (PG) in vitro is more extensive than the degradation affecting these polymers during ripening. We examined the hydrolysis of polygalacturonic acid and cell walls by PG isozyme 2 (PG2) under conditions widely adopted in the literature (pH 4.5 and containing Na+) and under conditions approximating the apoplastic environment of tomato fruit (pH 6.0 and K+ as the predominate cation). The pH optima for PG2 in the presence of K+ were 1.5 and 0.5 units higher for the hydrolysis of polygalacturonic acid and cell walls, respectively, compared with activity in the presence of Na+. Increasing K+ concentration stimulated pectin solubilization at pH 4.5 but had little influence at pH 6.0. Pectin depolymerization by PG2 was extensive at pH values from 4.0 to 5.0 and was further enhanced at high K+ levels. Oligomers were abundant products in in vitro reactions at pH 4.0 to 5.0, decreased sharply at pH 5.5, and were negligible at pH 6.0. EDTA stimulated PG-mediated pectin solubilization at pH 6.0 but did not promote oligomer production. Ca2+ suppressed PG-mediated pectin release at pH 4.5 yet had minimal influence on the proportional recovery of oligomers. Extensive pectin breakdown in processed tomato might be explained in part by cation- and low-pH-induced stimulation of PG and other wall-associated enzymes.

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Atmospheric conditions at the site of a cosmic ray observatory must be known for reconstructing observed extensive air showers. The Global Data Assimilation System (GDAS) is a global atmospheric model predicated on meteorological measurements and numerical weather predictions. GDAS provides altitude-dependent profiles of the main state variables of the atmosphere like temperature, pressure, and humidity. The original data and their application to the air shower reconstruction of the Pierre Auger Observatory are described. By comparisons with radiosonde and weather station measurements obtained on-site in Malargue and averaged monthly models, the utility of the GDAS data is shown. (C) 2012 Elsevier B.V. All rights reserved.

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The establishment of the dormant state in meristems involves considerable physiological and metabolic alterations necessary for surviving unfavourable growth conditions. However, a global molecular analysis of dormancy in meristems has been hampered by the difficulty in isolating meristem cells. We used cryosectioning to isolate purified cambial meristem cells from the woody plant Populus tremula during active growth and dormancy. These samples were used to generate meristem-specific cDNA libraries and for cDNA microarray experiments to define the global transcriptional changes underlying cambial dormancy. The results indicate a significant reduction in the complexity of the cambial transcriptome in the dormant state. Although cell division is terminated in the dormant cambium, the cell cycle machinery appears to be maintained in a skeletal state as suggested by the continued presence of transcripts for several cell cycle regulators. The downregulation of PttPIN1 and PttPIN2 transcripts explains the reduced basipetal polar auxin transport during dormancy. The induction of a member of the SINA family of ubiquitin ligases implicated in auxin signalling indicates a potential mechanism for modulation of auxin sensitivity during cambial dormancy. The metabolic alterations during dormancy are mirrored in the induction of genes involved in starch breakdown and the glyoxysomal cycle. Interestingly, the induction of RGA1 like gene suggests modification of gibberellin signalling in cambial dormancy. The induction of genes such as poplar orthologues of FIE and HAP2 indicates a potential role for these global regulators of transcription in orchestrating extensive changes in gene expression during dormancy.

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The phase equilibria in the Fe-Mg-Zn-O system in the temperature range 1100-1550degreesC in air have been experimentally studied using equilibration and quenching followed by electron probe X-ray microanalysis. The compositions of condensed phases in equilibrium in the binary MgO-ZnO system and the ternary Fe-Mg-O system have been reported at sub-solidus in air. Pseudo-ternary sections of the quaternary Fe-Mg-Zn-O system at 1100, 1250 and 1400degreesC in air were constructed using the experimental data. The solid solution of iron oxide, MgO and ZnO in the periclase (Mg, Zn, Fe)O, spinel (Mg2+, Fe2+, Zn2+)(x)Fe(2+y)3+O4 and zincite (Zn, Mg, Fe)O phases were found to be extensive under the conditions investigated. A continuous spinel solid solution is formed between the magnesioferrite (Mg2+, Fe2+)(x)Fe(2+y)3+O4 and franklinite (Zn2+, Fe2+)(x)Fe(2+y)3+O4 end-members at 1100 and 1250degreesC, extending to magnetite (Fe2+)(x)Fe(2+y)3+O4 at 1400degreesC in air. The compositions along the spinel boundaries were found to be non-stoichiometric, the magnitude of the non-stoichiometry being a function of composition and temperature in air. It was found that hematite dissolves neither MgO nor ZnO in air.

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Zincite and spinel phases are present in the complex slag systems encountered in zinc/lead sintering and zinc smelting processes. These phases form extensive solid solutions and are stable over a wide range of compositions, temperatures and oxygen partial pressures. Accurate information on the stability of these phases is required in order to develop thermodynamic models of these slag systems. Phase equilibria in the Fe–Zn–O system have been experimentally studied for a range of conditions, between 900°C and 1580°C and oxygen partial pressures (pO2) between air and metallic iron saturation, using equilibration and quenching techniques. The compositions of the phases were measured using Electron probe X-ray microanalysis (EPMA). The ferrous and ferric bulk iron concentrations were determined using a specially developed wet-chemical analysis procedure based on the use of ammonium metavanadate. XRD was used to confirm phase identification. A procedure was developed to overcome the problems associated with evaporation of zinc at low pO2 values and to ensure the achievement of equilibria. An isothermal section of the system FeO–Fe2O3–ZnO at high ZnO concentrations at 1200°C was constructed. The maximum solubilities of iron and zinc in zincite and spinel phases in equilibrium were determined at pO2 = 1 × 10-6 atm at 1200°C and 1300°C. The morphology of the zincite crystals sharply changes in air between 1200–1300°C from rounded to plate-like. This is shown to be associated with significant increase in total iron concentration, the additional iron being principally in the form of ferric iron. Calculations performed by FactSage with a thermodynamically optimised database have been compared with the experimental results.

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The storage of gases in porous adsorbents, such as activated carbon and carbon nanotubes, is examined here thermodynamically from a systems viewpoint, considering the entire adsorption-desorption cycle. The results provide concrete objective criteria to guide the search for the Holy Grail adsorbent, for which the adsorptive delivery is maximized. It is shown that, for ambient temperature storage of hydrogen and delivery between 30 and 1.5 bar pressure, for the optimum adsorbent the adsorption enthalpy change is 15.1 kJ/mol. For carbons, for which the average enthalpy change is typically 5.8 kJ/mol, an optimum operating temperature of about 115 K is predicted. For methane, an optimum enthalpy change of 18.8 kJ/mol is found, with the optimum temperature for carbons being 254 K. It is also demonstrated that for maximum delivery of the gas the optimum adsorbent must be homogeneous, and that introduction of heterogeneity, such as by ball milling, irradiation, and other means, can only provide small increases in physisorption-related delivery for hydrogen. For methane, heterogeneity is always detrimental, at any value of average adsorption enthalpy change. These results are confirmed with the help of experimental data from the literature, as well as extensive Monte Carlo simulations conducted here using slit pore models of activated carbons as well as atomistic models of carbon nanotubes. The simulations also demonstrate that carbon nanotubes offer little or no advantage over activated carbons in terms of enhanced delivery, when used as storage media for either hydrogen or methane.

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This thesis deals with the integration of the manpower criterion with the strategic decision making processes of technological projects in developing countries. This integration is to be achieved by ensuring the involvement of the actors, who have relevant roles and responsibilities along the whole life cycle of the project, in the strategic decision making phases of the project. The relevance of the actors is ascertained by the use of a responsibility index which relates their responsibility to the project's constituent stages. In the context of a technological project in a typical centrally-planned developing environment, the actors are identified as Arbiters, Planners, Implementors and Operators and their roles, concerns and objectives are derived. In this context, the actors are usually government and non-government organisations. Hence, decision making will involve multiple agencies as well as multiple criteria. A methodology covering the whole decision-making process, from options generation to options selection, and adopting Saaty's Analytical Hierarchy Process as an operational tool is proposed to deal with such multiple-criteria, multipleagency decision situations. The methodology is intended to integrate the consideration of the relevant criteria, the prevailing environmental and policy factors, and the concerns and objectives of the relevant actors into a unifying decision-making process which strives to facilitate enlightened decision making and to enhance learning and interaction. An extensive assessment of the methodology's feasibility, based on a specific technological project within the Iraqi oil industry is included, and indicates that the methodology should be both useful and implementable.

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IEEE 802.11 standard has achieved huge success in the past decade and is still under development to provide higher physical data rate and better quality of service (QoS). An important problem for the development and optimization of IEEE 802.11 networks is the modeling of the MAC layer channel access protocol. Although there are already many theoretic analysis for the 802.11 MAC protocol in the literature, most of the models focus on the saturated traffic and assume infinite buffer at the MAC layer. In this paper we develop a unified analytical model for IEEE 802.11 MAC protocol in ad hoc networks. The impacts of channel access parameters, traffic rate and buffer size at the MAC layer are modeled with the assistance of a generalized Markov chain and an M/G/1/K queue model. The performance of throughput, packet delivery delay and dropping probability can be achieved. Extensive simulations show the analytical model is highly accurate. From the analytical model it is shown that for practical buffer configuration (e.g. buffer size larger than one), we can maximize the total throughput and reduce the packet blocking probability (due to limited buffer size) and the average queuing delay to zero by effectively controlling the offered load. The average MAC layer service delay as well as its standard deviation, is also much lower than that in saturated conditions and has an upper bound. It is also observed that the optimal load is very close to the maximum achievable throughput regardless of the number of stations or buffer size. Moreover, the model is scalable for performance analysis of 802.11e in unsaturated conditions and 802.11 ad hoc networks with heterogenous traffic flows. © 2012 KSI.

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This paper proposes a new thermography-based maximum power point tracking (MPPT) scheme to address photovoltaic (PV) partial shading faults. Solar power generation utilizes a large number of PV cells connected in series and in parallel in an array, and that are physically distributed across a large field. When a PV module is faulted or partial shading occurs, the PV system sees a nonuniform distribution of generated electrical power and thermal profile, and the generation of multiple maximum power points (MPPs). If left untreated, this reduces the overall power generation and severe faults may propagate, resulting in damage to the system. In this paper, a thermal camera is employed for fault detection and a new MPPT scheme is developed to alter the operating point to match an optimized MPP. Extensive data mining is conducted on the images from the thermal camera in order to locate global MPPs. Based on this, a virtual MPPT is set out to find the global MPP. This can reduce MPPT time and be used to calculate the MPP reference voltage. Finally, the proposed methodology is experimentally implemented and validated by tests on a 600-W PV array.

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Multiple linear regression model plays a key role in statistical inference and it has extensive applications in business, environmental, physical and social sciences. Multicollinearity has been a considerable problem in multiple regression analysis. When the regressor variables are multicollinear, it becomes difficult to make precise statistical inferences about the regression coefficients. There are some statistical methods that can be used, which are discussed in this thesis are ridge regression, Liu, two parameter biased and LASSO estimators. Firstly, an analytical comparison on the basis of risk was made among ridge, Liu and LASSO estimators under orthonormal regression model. I found that LASSO dominates least squares, ridge and Liu estimators over a significant portion of the parameter space for large dimension. Secondly, a simulation study was conducted to compare performance of ridge, Liu and two parameter biased estimator by their mean squared error criterion. I found that two parameter biased estimator performs better than its corresponding ridge regression estimator. Overall, Liu estimator performs better than both ridge and two parameter biased estimator.

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We investigated controls on the water chemistry of a South Ecuadorian cloud forest catchment which is partly pristine, and partly converted to extensive pasture. From April 2007 to May 2008 water samples were taken weekly to biweekly at nine different subcatchments, and were screened for differences in electric conductivity, pH, anion, as well as element composition. A principal component analysis was conducted to reduce dimensionality of the data set and define major factors explaining variation in the data. Three main factors were isolated by a subset of 10 elements (Ca2+, Ce, Gd, K+, Mg2+, Na+, Nd, Rb, Sr, Y), explaining around 90% of the data variation. Land-use was the major factor controlling and changing water chemistry of the subcatchments. A second factor was associated with the concentration of rare earth elements in water, presumably highlighting other anthropogenic influences such as gravel excavation or road construction. Around 12% of the variation was explained by the third component, which was defined by the occurrence of Rb and K and represents the influence of vegetation dynamics on element accumulation and wash-out. Comparison of base- and fast flow concentrations led to the assumption that a significant portion of soil water from around 30 cm depth contributes to storm flow, as revealed by increased rare earth element concentrations in fast flow samples. Our findings demonstrate the utility of multi-tracer principal component analysis to study tropical headwater streams, and emphasize the need for effective land management in cloud forest catchments.

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Energy policies around the world are mandating for a progressive increase in renewable energy production. Extensive grassland areas with low productivity and land use limitations have become target areas for sustainable energy production to avoid competition with food production on the limited available arable land resources and minimize further conversion of grassland into intensively managed energy cropping systems or abandonment. However, the high spatio-temporal variability in botanical composition and biochemical parameters is detrimental to reliable assessment of biomass yield and quality regarding anaerobic digestion. In an approach to assess the performance for predicting biomass using a multi-sensor combination including NIRS, ultra-sonic distance measurements and LAI-2000, biweekly sensor measurements were taken on a pure stand of reed canary grass (Phalaris aruninacea), a legume grass mixture and a diversity mixture with thirty-six species in an experimental extensive two cut management system. Different combinations of the sensor response values were used in multiple regression analysis to improve biomass predictions compared to exclusive sensors. Wavelength bands for sensor specific NDVI-type vegetation indices were selected from the hyperspectral data and evaluated for the biomass prediction as exclusive indices and in combination with LAI and ultra-sonic distance measurements. Ultrasonic sward height was the best to predict biomass in single sensor approaches (R² 0.73 – 0.76). The addition of LAI-2000 improved the prediction performance by up to 30% while NIRS barely improved the prediction performance. In an approach to evaluate broad based prediction of biochemical parameters relevant for anaerobic digestion using hyperspectral NIRS, spectroscopic measurements were taken on biomass from the Jena-Experiment plots in 2008 and 2009. Measurements were conducted on different conditions of the biomass including standing sward, hay and silage and different spectroscopic devices to simulate different preparation and measurement conditions along the process chain for biogas production. Best prediction results were acquired for all constituents at laboratory measurement conditions with dried and ground samples on a bench-top NIRS system (RPD > 3) with a coefficient of determination R2 < 0.9. The same biomass was further used in batch fermentation to analyse the impact of species richness and functional group composition on methane yields using whole crop digestion and pressfluid derived by the Integrated generation of solid Fuel and Biogas from Biomass (IFBB) procedure. Although species richness and functional group composition were largely insignificant, the presence of grasses and legumes in the mixtures were most determining factors influencing methane yields in whole crop digestion. High lignocellulose content and a high C/N ratio in grasses may have reduced the digestibility in the first cut material, excess nitrogen may have inhibited methane production in second cut legumes, while batch experiments proved superior specific methane yields of IFBB press fluids and showed that detrimental effects of the parent material were reduced by the technical treatment

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Contemporary integrated circuits are designed and manufactured in a globalized environment leading to concerns of piracy, overproduction and counterfeiting. One class of techniques to combat these threats is circuit obfuscation which seeks to modify the gate-level (or structural) description of a circuit without affecting its functionality in order to increase the complexity and cost of reverse engineering. Most of the existing circuit obfuscation methods are based on the insertion of additional logic (called “key gates”) or camouflaging existing gates in order to make it difficult for a malicious user to get the complete layout information without extensive computations to determine key-gate values. However, when the netlist or the circuit layout, although camouflaged, is available to the attacker, he/she can use advanced logic analysis and circuit simulation tools and Boolean SAT solvers to reveal the unknown gate-level information without exhaustively trying all the input vectors, thus bringing down the complexity of reverse engineering. To counter this problem, some ‘provably secure’ logic encryption algorithms that emphasize methodical selection of camouflaged gates have been proposed previously in literature [1,2,3]. The contribution of this paper is the creation and simulation of a new layout obfuscation method that uses don't care conditions. We also present proof-of-concept of a new functional or logic obfuscation technique that not only conceals, but modifies the circuit functionality in addition to the gate-level description, and can be implemented automatically during the design process. Our layout obfuscation technique utilizes don’t care conditions (namely, Observability and Satisfiability Don’t Cares) inherent in the circuit to camouflage selected gates and modify sub-circuit functionality while meeting the overall circuit specification. Here, camouflaging or obfuscating a gate means replacing the candidate gate by a 4X1 Multiplexer which can be configured to perform all possible 2-input/ 1-output functions as proposed by Bao et al. [4]. It is important to emphasize that our approach not only obfuscates but alters sub-circuit level functionality in an attempt to make IP piracy difficult. The choice of gates to obfuscate determines the effort required to reverse engineer or brute force the design. As such, we propose a method of camouflaged gate selection based on the intersection of output logic cones. By choosing these candidate gates methodically, the complexity of reverse engineering can be made exponential, thus making it computationally very expensive to determine the true circuit functionality. We propose several heuristic algorithms to maximize the RE complexity based on don’t care based obfuscation and methodical gate selection. Thus, the goal of protecting the design IP from malicious end-users is achieved. It also makes it significantly harder for rogue elements in the supply chain to use, copy or replicate the same design with a different logic. We analyze the reverse engineering complexity by applying our obfuscation algorithm on ISCAS-85 benchmarks. Our experimental results indicate that significant reverse engineering complexity can be achieved at minimal design overhead (average area overhead for the proposed layout obfuscation methods is 5.51% and average delay overhead is about 7.732%). We discuss the strengths and limitations of our approach and suggest directions that may lead to improved logic encryption algorithms in the future. References: [1] R. Chakraborty and S. Bhunia, “HARPOON: An Obfuscation-Based SoC Design Methodology for Hardware Protection,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 28, no. 10, pp. 1493–1502, 2009. [2] J. A. Roy, F. Koushanfar, and I. L. Markov, “EPIC: Ending Piracy of Integrated Circuits,” in 2008 Design, Automation and Test in Europe, 2008, pp. 1069–1074. [3] J. Rajendran, M. Sam, O. Sinanoglu, and R. Karri, “Security Analysis of Integrated Circuit Camouflaging,” ACM Conference on Computer Communications and Security, 2013. [4] Bao Liu, Wang, B., "Embedded reconfigurable logic for ASIC design obfuscation against supply chain attacks,"Design, Automation and Test in Europe Conference and Exhibition (DATE), 2014 , vol., no., pp.1,6, 24-28 March 2014.

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The air fluorescence detector of the Pierre Auger Observatory is designed to perforin calorimetric measurements of extensive air showers created by Cosmic rays of above 10(18) eV. To correct these measurements for the effects introduced by atmospheric fluctuations, the Observatory contains a group Of monitoring instruments to record atmospheric conditions across the detector site, ail area exceeding 3000 km(2). The atmospheric data are used extensively in the reconstruction of air showers, and are particularly important for the correct determination of shower energies and the depths of shower maxima. This paper contains a summary of the molecular and aerosol conditions measured at the Pierre Auger Observatory since the start of regular operations in 2004, and includes a discussion of the impact of these measurements oil air shower reconstructions. Between 10(18) and 10(20) eV, the systematic Uncertainties due to all atmospheric effects increase from 4% to 8% in measurements of shower energy, and 4 g cm(-2) to 8 g cm(-2) in measurements of the shower maximum. (C) 2010 Elsevier B.V. All rights reserved.