83 resultados para SHARP DIFFRACTION PEAK


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We report the investigation of the mechanical properties of different types of amyloid fibrils by the peak force quantitative nanomechanical (PF-QNM) technique. We demonstrate that this technique correctly measures the Young’s modulus independent of the polymorphic state and the cross-sectional structural details of the fibrils, and we show that values for amyloid fibrils assembled from heptapeptides, a-synuclein, Ab(1–42), insulin, b-lactoglobulin,lysozyme, ovalbumin, Tau protein and bovine serum albumin all fall in the range of 2–4 GPa.

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For decades regulators in the energy sector have focused on facilitating the maximisation of energy supply in order to meet demand through liberalisation and removal of market barriers. The debate on climate change has emphasised a new type of risk in the balance between energy demand and supply: excessively high energy demand brings about significantly negative environmental and economic impacts. This is because if a vast number of users is consuming electricity at the same time, energy suppliers have to activate dirty old power plants with higher greenhouse gas emissions and higher system costs. The creation of a Europe-wide electricity market requires a systematic investigation into the risk of aggregate peak demand. This paper draws on the e-Living Time-Use Survey database to assess the risk of aggregate peak residential electricity demand for European energy markets. Findings highlight in which countries and for what activities the risk of aggregate peak demand is greater. The discussion highlights which approaches energy regulators have started considering to convince users about the risks of consuming too much energy during peak times. These include ‘nudging’ approaches such as the roll-out of smart meters, incentives for shifting the timing of energy consumption, differentiated time-of-use tariffs, regulatory financial incentives and consumption data sharing at the community level.

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We show that the four-dimensional variational data assimilation method (4DVar) can be interpreted as a form of Tikhonov regularization, a very familiar method for solving ill-posed inverse problems. It is known from image restoration problems that L1-norm penalty regularization recovers sharp edges in the image more accurately than Tikhonov, or L2-norm, penalty regularization. We apply this idea from stationary inverse problems to 4DVar, a dynamical inverse problem, and give examples for an L1-norm penalty approach and a mixed total variation (TV) L1–L2-norm penalty approach. For problems with model error where sharp fronts are present and the background and observation error covariances are known, the mixed TV L1–L2-norm penalty performs better than either the L1-norm method or the strong constraint 4DVar (L2-norm)method. A strength of the mixed TV L1–L2-norm regularization is that in the case where a simplified form of the background error covariance matrix is used it produces a much more accurate analysis than 4DVar. The method thus has the potential in numerical weather prediction to overcome operational problems with poorly tuned background error covariance matrices.

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Upper Cenomanian pelagic sediments from the northern Alpine Helvetic fold-and-thrust belt (northern Tethyan margin) coeval with Oceanic Anoxic Event (OAE) 2 are characterized by the temporal persistence of micrite sedimentation and lack of organic carbon-rich layers. We studied an expanded section in the Chrummflueschlucht (east of Euthal, Switzerland), which encompasses the OAE 2 time interval. In order to identify the paleoceanographic and paleoenvironmental conditions during OAE 2 in this part of the northern Tethyan margin, and more specifically to trace eventual changes in nutrient levels and oxic conditions, we investigated the biostratigraphy (planktonic foraminifera), the bulk-rock mineralogy, and measured stable carbon- and oxygen-isotopes, total phosphorus (P) and redox-sensitive trace-element (RSTE) contents. We were able to determine – with some remaining uncertainties – the different planktonic foraminiferal biozones characteristic of the Cenomanian–Turonian boundary interval (Rotalipora cushmani, Whiteinella archaeocretacea and Helvetoglobotruncana helvetica zones). In the lower part of the section (R. cushmani total range zone), the bulk-rock δ13C record shows a long-term increase. Within sediments attributed to the W. archaeocretacea partial range zone, δ13C values reach a maximum of 3.3‰ (peak “a”). In the following the values decrease and increase again to arrive at a plateau with high δ13C values of around 3.1‰, which ends with a peak of 3.3‰ (peak “c”). At the top of the section, in sediments belonging to the H. helvetica total range zone, δ13C values decrease to post-OAE values of around 2.2‰. The last occurrence of R. cushmani is observed just above the positive δ13C shift characterizing OAE 2. P contents display small variations along the section with a long-term decreasing trend towards the top. Before the OAE 2 interval, P values show higher values and relatively good covariation with detrital input, indicating higher nutrient input before OAE 2. In sediments corresponding to the onset of the δ13C positive excursion, P content is marked by a sharp peak probably linked to a slowdown in sedimentation rates and/or the presence of a small hiatus, as is shown by the presence of glauconite and phosphatic grains. In the interval corresponding to OAE 2, P values remain low and increase slightly at the end of the positive shift in the δ13C record (in the H. helvetica total range zone). The average contents of RSTE (U, V, As, Co, Mo and Mn) remain low throughout the section and appreciable RSTE enrichments have not been observed for the sedimentary interval corresponding to OAE 2. No correlation is observed with stratigraphic trends in RSTE contents in organic-rich deeper-water sections. The presence of double-keeled planktonic foraminifera species during most of the Cenomanian/Turonian boundary event is another evidence of relatively well-oxygenated conditions in this part of the northern Tethyan outer shelf. Our results show that the Chrummflueschlucht section corresponds to one of the most complete section for the Cenomanian–Turonian boundary interval known from the Helvetic realm even if a small hiatus may be present at the onset of the δ13C record (peak “a”). The evolution of P contents suggests an increase in input of this nutritive element at the onset of OAE2. However, the trends in RSTE contents and the planktonic foraminifera assemblages show that the Helvetic realm has not been affected by strongly depleted oxygen conditions during OAE 2.

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The internal variability and coupling between the stratosphere and troposphere in CCMVal‐2 chemistry‐climate models are evaluated through analysis of the annular mode patterns of variability. Computation of the annular modes in long data sets with secular trends requires refinement of the standard definition of the annular mode, and a more robust procedure that allows for slowly varying trends is established and verified. The spatial and temporal structure of the models’ annular modes is then compared with that of reanalyses. As a whole, the models capture the key features of observed intraseasonal variability, including the sharp vertical gradients in structure between stratosphere and troposphere, the asymmetries in the seasonal cycle between the Northern and Southern hemispheres, and the coupling between the polar stratospheric vortices and tropospheric midlatitude jets. It is also found that the annular mode variability changes little in time throughout simulations of the 21st century. There are, however, both common biases and significant differences in performance in the models. In the troposphere, the annular mode in models is generally too persistent, particularly in the Southern Hemisphere summer, a bias similar to that found in CMIP3 coupled climate models. In the stratosphere, the periods of peak variance and coupling with the troposphere are delayed by about a month in both hemispheres. The relationship between increased variability of the stratosphere and increased persistence in the troposphere suggests that some tropospheric biases may be related to stratospheric biases and that a well‐simulated stratosphere can improve simulation of tropospheric intraseasonal variability.

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Microcontroller-based peak current mode control of a buck converter is investigated. The new solution uses a discrete time controller with digital slope compensation. This is implemented using only a single-chip microcontroller to achieve desirable cycle-by-cycle peak current limiting. The digital controller is implemented as a two-pole, two-zero linear difference equation designed using a continuous time model of the buck converter and a discrete time transform. Subharmonic oscillations are removed with digital slope compensation using a discrete staircase ramp. A 16 W hardware implementation directly compares analog and digital control. Frequency response measurements are taken and it is shown that the crossover frequency and expected phase margin of the digital control system match that of its analog counterpart.

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The structures of 2-hydroxybenzamide(C7H7NO2) and 2-methoxybenzamide (C8H9NO2) have been determined in the gas-phase by electron diffraction using results from quantum chemical calculations to inform restraints used on the structural parameters. Theoretical methods (HF and MP2/6-311+G(d,p)) predict four stable conformers for both 2-hydroxybenzamide and 2-methoxybenzamide. For both compounds, evidence for intramolecular hydrogen bonding is presented. In 2-hydroxybenzamide, the observed hydrogen bonded fragment is between the hydroxyl and carbonyl groups, while in 2-methoxybenzamide, the hydrogen bonded fragment is between one of the hydrogen atoms of the amide group and the methoxy oxygen atom.

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We propose a Nystr¨om/product integration method for a class of second kind integral equations on the real line which arise in problems of two-dimensional scalar and elastic wave scattering by unbounded surfaces. Stability and convergence of the method is established with convergence rates dependent on the smoothness of components of the kernel. The method is applied to the problem of acoustic scattering by a sound soft one-dimensional surface which is the graph of a function f, and superalgebraic convergence is established in the case when f is infinitely smooth. Numerical results are presented illustrating this behavior for the case when f is periodic (the diffraction grating case). The Nystr¨om method for this problem is stable and convergent uniformly with respect to the period of the grating, in contrast to standard integral equation methods for diffraction gratings which fail at a countable set of grating periods.

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X-ray resonant scattering has been exploited to investigate the crystal structure of the AB1.5Te1.5 phases (A = Co, Rh, Ir; B = Ge, Sn). Analysis of the diffraction data reveals that CoGe1.5Te1.5 and ASn1.5Te1.5 adopt a rhombohedral skutterudite-related structure, containing diamond-shape B2Te2 rings, in which the B and Te atoms are ordered and trans to each other. Anion ordering is however incomplete, and with increasing the size of both cations and anions, the degree of anion ordering decreases. By contrast, the diffraction data of IrGe1.5Te1.5 are consistent with an almost statistical distribution of the anions over the available sites, although some ordered domains may be present. The thermoelectric properties of these materials are discussed in the light of these results.

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Energy storage is a potential alternative to conventional network reinforcementof the low voltage (LV) distribution network to ensure the grid’s infrastructure remainswithin its operating constraints. This paper presents a study on the control of such storagedevices, owned by distribution network operators. A deterministic model predictive control (MPC) controller and a stochastic receding horizon controller (SRHC) are presented, wherethe objective is to achieve the greatest peak reduction in demand, for a given storagedevice specification, taking into account the high level of uncertainty in the prediction of LV demand. The algorithms presented in this paper are compared to a standard set-pointcontroller and bench marked against a control algorithm with a perfect forecast. A specificcase study, using storage on the LV network, is presented, and the results of each algorithmare compared. A comprehensive analysis is then carried out simulating a large number of LV networks of varying numbers of households. The results show that the performance of each algorithm is dependent on the number of aggregated households. However, on a typical aggregation, the novel SRHC algorithm presented in this paper is shown to outperform each of the comparable storage control techniques.

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The Distribution Network Operators (DNOs) role is becoming more difficult as electric vehicles and electric heating penetrate the network, increasing the demand. As a result it becomes harder for the distribution networks infrastructure to remain within its operating constraints. Energy storage is a potential alternative to conventional network reinforcement such as upgrading cables and transformers. The research presented here in this paper shows that due to the volatile nature of the LV network, the control approach used for energy storage has a significant impact on performance. This paper presents and compares control methodologies for energy storage where the objective is to get the greatest possible peak demand reduction across the day from a pre-specified storage device. The results presented show the benefits and detriments of specific types of control on a storage device connected to a single phase of an LV network, using aggregated demand profiles based on real smart meter data from individual homes. The research demonstrates an important relationship between how predictable an aggregation is and the best control methodology required to achieve the objective.

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Reinforcing the Low Voltage (LV) distribution network will become essential to ensure it remains within its operating constraints as demand on the network increases. The deployment of energy storage in the distribution network provides an alternative to conventional reinforcement. This paper presents a control methodology for energy storage to reduce peak demand in a distribution network based on day-ahead demand forecasts and historical demand data. The control methodology pre-processes the forecast data prior to a planning phase to build in resilience to the inevitable errors between the forecasted and actual demand. The algorithm uses no real time adjustment so has an economical advantage over traditional storage control algorithms. Results show that peak demand on a single phase of a feeder can be reduced even when there are differences between the forecasted and the actual demand. In particular, results are presented that demonstrate when the algorithm is applied to a large number of single phase demand aggregations that it is possible to identify which of these aggregations are the most suitable candidates for the control methodology.

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The propagation of 7.335 MHz, c.w. signals over a 5212 km sub-auroral, west-east path is studied. Measurements and semi-empirical predictions are made of the amplitude distributions and Doppler shifts of the received signals. The observed amplitude distribution is fitted with one produced by a numerical fading model, yielding the power losses suffered by the signals during propagation via the predominating modes. The signals are found to suffer exceptionally low losses at certain local times under geomagnetically quiet conditions. The mid-latitude trough in the F2 peak ionization density is predicted by a statistical model to be at the latitudes of this path at these times and at low Kp values. A sharp cut-off in low-power losses at a mean Kp of 2.75 strongly implicates the trough in the propagation of these signals. The Doppler shifts observed at these times cannot be explained by a simple ray-tracing model. It is shown however, that a simple extension of this model to allow for the trough can reproduce the form of the observed diurnal variation.

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Solving pharmaceutical crystal structures from powder diffraction data is discussed in terms of the methodologies that have been applied and the complexity of the structures that have been solved. The principles underlying these methodologies are summarized and representative examples of polymorph, solvate, salt and cocrystal structure solutions are provided, together with examples of some particularly challenging structure determinations.

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This study describes a simple technique that improves a recently developed 3D sub-diffraction imaging method based on three-photon absorption of commercially available quantum dots. The method combines imaging of biological samples via tri-exciton generation in quantum dots with deconvolution and spectral multiplexing, resulting in a novel approach for multi-color imaging of even thick biological samples at a 1.4 to 1.9-fold better spatial resolution. This approach is realized on a conventional confocal microscope equipped with standard continuous-wave lasers. We demonstrate the potential of multi-color tri-exciton imaging of quantum dots combined with deconvolution on viral vesicles in lentivirally transduced cells as well as intermediate filaments in three-dimensional clusters of mouse-derived neural stem cells (neurospheres) and dense microtubuli arrays in myotubes formed by stacks of differentiated C2C12 myoblasts.