A second-order scheme with nonuniform time steps for a linear reaction-subdiffusion problem

It is reasonable to assume that a discrete convolution structure dominates the local truncation error of any numerical Caputo formula because the fractional time derivative and its discrete approximation have the same convolutional form. We suggest an error convolution structure (ECS) analysis for a class of interpolation-type approximations to the Caputo fractional derivative. Our assumptions permit the use of adaptive time steps, such as is appropriate for accurately resolving the initial singularity of the solution and also certain complex behavior away from the initial time. The ECS analysis of numerical approximations has two advantages: (i) to localize (and simplify) the analysis of the approximation error of a discrete convolution formula on general nonuniform time grids; and (ii) to reveal the error distribution information in the long-time integration via the global consistency error. The core result in this paper is an ECS bound and a global consistency analysis of the nonuniform Alikhanov approximation, which is constructed at an offset point by using linear and quadratic polynomial interpolation. Using this result, we derive a sharp L2-norm error estimate of a second-order Crank-Nicolson-like scheme for linear reaction-subdiffusion problems. An example is presented to show the sharpness of our analysis

Magnetic coupling properties of rare-earth metals (Gd, Nd) doped ZnO: first-principles calculations

The electronic structure and magnetic coupling properties of rare-earth metals (Gd, Nd) doped ZnO have been investigated using first-principles methods. We show that the magnetic coupling between Gd or Nd ions in the nearest neighbor sites is ferromagnetic. The stability of the ferromagnetic coupling between Gd ions can be enhanced by appropriate electron doping into ZnO:Gd system and the room-temperature ferromagnetism can be achieved. However, for ZnO:Nd system, the ferromagnetism between Nd ions can be enhanced by appropriate holes doping into the sample. The room-temperature ferromagnetism can also be achieved in the \emph{n}-conducting ZnO:Nd sample. Our calculated results are in good agreement with the conclusions of the recent experiments. The effect of native defects (V$_{\rm{Zn}}$, V$_{\rm{O}}$) on the ferromagnetism is also discussed.Comment: 5 pages, 5 figure

Machine-Learning-Assisted Design of a Robust Biomimetic Radiative Cooling Metamaterial

Recently, biomimetic photonic structural materials have significantly improved their radiative cooling performance. However, most research has focused on understanding cooling mechanisms, with limited exploration of sensitive parameter variations. Traditional numerical methods are costly and time-consuming and often struggle to identify optimal solutions, limiting the scope of high-performance microstructure design. To address these challenges, we integrated machine learning into the design of Batocera LineolataHope bionic photonic structures, using SiO2 as the substrate. Deep learning models provided insights into the complex relationship between bionic metamaterials and their spectral response, enabling us to identify the optimal performance parameter range for truncated cone arrays (height-to-diameter ratio (H/D-bottom) from 0.8 to 2.4), achieving a high average emissivity of 0.985. Experimentally, the noon temperature of fabricated samples decreased by about 8.3 degrees C. This data-driven approach accelerates the design and optimization of robust biomimetic radiative cooling metamaterials, promising significant advancements in standardized passive radiative cooling applications

Re: the role of radiology in anatomy teaching in UK medical schools: a national survey. A reply.

Sir – We thank Raja and colleagues1 for their interest in our article and share their enthusiasm for the integration of radiology in anatomy teaching. This is something that we feel passionate about. Two of our authors are full-time practicing consultant radiologists with additional roles as medical educators in anatomy teaching at the University of Cambridge medical school

The wavelet-NARMAX representation : a hybrid model structure combining polynomial models with multiresolution wavelet decompositions

A new hybrid model structure combing polynomial models with multiresolution wavelet decompositions is introduced for nonlinear system identification. Polynomial models play an important role in approximation theory, and have been extensively used in linear and nonlinear system identification. Wavelet decompositions, in which the basis functions have the property of localization in both time and frequency, outperform many other approximation schemes and offer a flexible solution for approximating arbitrary functions. Although wavelet representations can approximate even severe nonlinearities in a given signal very well, the advantage of these representations can be lost when wavelets are used to capture linear or low-order nonlinear behaviour in a signal. In order to sufficiently utilise the global property of polynomials and the local property of wavelet representations simultaneously, in this study polynomial models and wavelet decompositions are combined together in a parallel structure to represent nonlinear input-output systems. As a special form of the NARMAX model, this hybrid model structure will be referred to as the WAvelet-NARMAX model, or simply WANARMAX. Generally, such a WANARMAX representation for an input-output system might involve a large number of basis functions and therefore a great number of model terms. Experience reveals that only a small number of these model terms are significant to the system output. A new fast orthogonal least squares algorithm, called the matching pursuit orthogonal least squares (MPOLS) algorithm, is also introduced in this study to determine which terms should be included in the final model

Judgement and supply chain dynamics

Forecasting demand at the individual stock-keeping-unit (SKU) level often necessitates the use of statistical methods, such as exponential smoothing. In some organizations, however, statistical forecasts will be subject to judgemental adjustments by managers. Although a number of empirical and ‘laboratory’ studies have been performed in this area, no formal OR modelling has been conducted to offer insights into the impact such adjustments may have on supply chain performance and the potential development of mitigation mechanisms. This is because of the associated dynamic complexity and the situation-specific nature of the problem at hand. In conjunction with appropriate stock control rules, demand forecasts help decide how much to order. It is a common practice that replenishment orders may also be subject to judgemental intervention, adding further to the dynamic system complexity and interdependence. The system dynamics (SD) modelling method can help advance knowledge in this area, where mathematical modelling cannot accommodate the associated complexity. This study, which constitutes part of a UK government funded (EPSRC) project, uses SD models to evaluate the effects of forecasting and ordering adjustments for a wide set of scenarios involving: three different inventory policies; seven different (combinations of) points of intervention; and four different (combinations of) types of judgmental intervention (optimistic and pessimistic). The results enable insights to be gained into the performance of the entire supply chain. An agenda for further research concludes the paper

A RAMP marker linked to the tobacco black shank resistant gene

Bulk segregant analysis (BSA) and randomly amplified microsatellite polymorphism (RAMP) were employed to analyze F2 individuals of the Yunyan 317×Hubei 517 to screen and characterize molecularmarkers linked to black shank resistant gene. A total of 800 arbitrary decamer oligonucleotide primerpairs were used for RAMP analysis. Primer pair GT (CA) 4/S89, producing one RAMP marker GT (CA)4/S89550, was tightly linked to the black shank resistant gene. Results of Southern blot suggest that the fragment GT (CA) 4/S89550 was existed in Yunyan 317 and resistant plants, and absent in Hubei 517.Linkage analysis was carried out using marker GT (CA) 4/S89550 on 752 black shank high-resistant individuals of F2 progenies from crossing between Yunyan 317 and Hubei 517. Our results indicated thatthe genetic distances between GT (CA) 4/S89550 and black shank resistant gene was 1.4cM

Development of 〈110〉 texture in copper thin films

Author name used in this publication: C. H. Woo2001-2002 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Unusual Formation of Point-Defect Complexes in the Ultrawide-Band-Gap Semiconductor β-Ga2 O3

Understanding the unique properties of ultra-wide band gap semiconductors requires detailed information about the exact nature of point defects and their role in determining the properties. Here, we report the first direct microscopic observation of an unusual formation of point defect complexes within the atomic-scale structure of β-Ga2O3 using high resolution scanning transmission electron microscopy (STEM). Each complex involves one cation interstitial atom paired with two cation vacancies. These divacancy-interstitial complexes correlate directly with structures obtained by density functional theory, which predicts them to be compensating acceptors in β-Ga2O3. This prediction is confirmed by a comparison between STEM data and deep level optical spectroscopy results, which reveals that these complexes correspond to a deep trap within the band gap, and that the development of the complexes is facilitated by Sn doping through increased vacancy concentration. These findings provide new insight on this emerging material's unique response to the incorporation of impurities that can critically influence their properties