Optical transitions and nature of Stokes shift in spherical CdS quantum dots

We study the structure of the energy spectra along with the character of the states participating in optical transitions in colloidal CdS quantum dots (QDs) using the {\sl ab initio} accuracy charge patching method combined with the %pseudopotential based folded spectrum calculations of electronic structure of thousand-atom nanostructures. In particular, attention is paid to the nature of the large resonant Stokes shift observed in CdS quantum dots. We find that the top of the valence band state is bright, in contrast with the results of numerous {\bf k$\cdot$p} calculations, and determine the limits of applicability of the {\bf k$\cdot$p} approach. The calculated electron-hole exchange splitting suggests the spin-forbidden valence state may explain the nature of the ``dark exciton'' in CdS quantum dots.Comment: 5 pages, 4 figure

Efficient Active Learning for Image Classification and Segmentation using a Sample Selection and Conditional Generative Adversarial Network

Training robust deep learning (DL) systems for medical image classification or segmentation is challenging due to limited images covering different disease types and severity. We propose an active learning (AL) framework to select most informative samples and add to the training data. We use conditional generative adversarial networks (cGANs) to generate realistic chest xray images with different disease characteristics by conditioning its generation on a real image sample. Informative samples to add to the training set are identified using a Bayesian neural network. Experiments show our proposed AL framework is able to achieve state of the art performance by using about 35% of the full dataset, thus saving significant time and effort over conventional methods

Knowledge based cloud FE simulation of sheet metal forming processes

The use of Finite Element (FE) simulation software to adequately predict the outcome of sheet metal forming processes is crucial to enhancing the efficiency and lowering the development time of such processes, whilst reducing costs involved in trial-and-error prototyping. Recent focus on the substitution of steel components with aluminum alloy alternatives in the automotive and aerospace sectors has increased the need to simulate the forming behavior of such alloys for ever more complex component geometries. However these alloys, and in particular their high strength variants, exhibit limited formability at room temperature, and high temperature manufacturing technologies have been developed to form them. Consequently, advanced constitutive models are required to reflect the associated temperature and strain rate effects. Simulating such behavior is computationally very expensive using conventional FE simulation techniques. This paper presents a novel Knowledge Based Cloud FE (KBC-FE) simulation technique that combines advanced material and friction models with conventional FE simulations in an efficient manner thus enhancing the capability of commercial simulation software packages. The application of these methods is demonstrated through two example case studies, namely: the prediction of a material's forming limit under hot stamping conditions, and the tool life prediction under multi-cycle loading conditions

Models for the magnetic ac susceptibility of granular superferromagnetic CoFe/Al2_2O3_3

The magnetization and magnetic ac susceptibility, $\chi = \chi' - i \chi''$, of superferromagnetic systems are studied by numerical simulations. The Cole-Cole plot, $\chi''$ vs. $\chi'$, is used as a tool for classifying magnetic systems by their dynamical behavior. The simulations of the magnetization hysteresis and the ac susceptibility are performed with two approaches for a driven domain wall in random media. The studies are motivated by recent experimental results on the interacting nanoparticle system Co$_{80}$Fe$_{20}$/Al$_{2}$O$_{3}$ showing superferromagnetic behavior. Its Cole-Cole plot indicates domain wall motion dynamics similarly to a disordered ferromagnet, including pinning and sliding motion. With our models we can successfully reproduce the features found in the experimental Cole-Cole plots.Comment: 8 pages, 6 figure

Cooling of Nanomechanical Resonator Based on Periodical Coupling to Cooper Pair Box

We propose and study an active cooling mechanism for the nanomechanical resonator (NAMR) based on periodical coupling to a Cooper pair box (CPB), which is implemented by a designed series of magnetic flux pluses threading through the CPB. When the initial phonon number of the NAMR is not too large, this cooling protocol is efficient in decreasing the phonon number by two to three orders of magnitude. Our proposal is theoretically universal in cooling various boson systems of single mode. It can be specifically generalized to prepare the nonclassical state of the NAMR.Comment: 5pages,3figure

The Fourth Element: Characteristics, Modelling, and Electromagnetic Theory of the Memristor

In 2008, researchers at HP Labs published a paper in {\it Nature} reporting the realisation of a new basic circuit element that completes the missing link between charge and flux-linkage, which was postulated by Leon Chua in 1971. The HP memristor is based on a nanometer scale TiO$_2$ thin-film, containing a doped region and an undoped region. Further to proposed applications of memristors in artificial biological systems and nonvolatile RAM (NVRAM), they also enable reconfigurable nanoelectronics. Moreover, memristors provide new paradigms in application specific integrated circuits (ASICs) and field programmable gate arrays (FPGAs). A significant reduction in area with an unprecedented memory capacity and device density are the potential advantages of memristors for Integrated Circuits (ICs). This work reviews the memristor and provides mathematical and SPICE models for memristors. Insight into the memristor device is given via recalling the quasi-static expansion of Maxwell's equations. We also review Chua's arguments based on electromagnetic theory.Comment: 28 pages, 14 figures, Accepted as a regular paper - the Proceedings of Royal Society

On Solving a Generalized Chinese Remainder Theorem in the Presence of Remainder Errors

In estimating frequencies given that the signal waveforms are undersampled multiple times, Xia et. al. proposed to use a generalized version of Chinese remainder Theorem (CRT), where the moduli are $M_1, M_2, \cdots, M_k$ which are not necessarily pairwise coprime. If the errors of the corrupted remainders are within \tau=\sds \max_{1\le i\le k} \min_{\stackrel{1\le j\le k}{j\neq i}} \frac{\gcd(M_i,M_j)}4, their schemes can be used to construct an approximation of the solution to the generalized CRT with an error smaller than $\tau$. Accurately finding the quotients is a critical ingredient in their approach. In this paper, we shall start with a faithful historical account of the generalized CRT. We then present two treatments of the problem of solving generalized CRT with erroneous remainders. The first treatment follows the route of Wang and Xia to find the quotients, but with a simplified process. The second treatment considers a simplified model of generalized CRT and takes a different approach by working on the corrupted remainders directly. This approach also reveals some useful information about the remainders by inspecting extreme values of the erroneous remainders modulo $4\tau$. Both of our treatments produce efficient algorithms with essentially optimal performance. Finally, this paper constructs a counterexample to prove the sharpness of the error bound $\tau$

IDENTIFYING FREQUENT SEAFOOD PURCHASERS IN THE NORTHEASTERN U.S.

Factors affecting the frequency of purchase of fish and other seafood for at-home and restaurant consumption by Northeastern consumers were investigated. Cluster analysis identified six groups of consumers with similar perceptions of the attributes of fish. Demographic and cluster membership variables were employed in logistic regressions to identify the characteristics of frequent at-home use and restaurant purchasers. At-home purchase was more likely to be frequent among respondents with white collar occupations, older ages, urban/suburban and New England residence, recreational fishing participation, and membership in one of five attitudinal clusters. Restaurant purchase was more likely to be frequent among whites and among those with higher incomes, white collar occupations, recreational fishing involvement and among members of two clusters with favorable attitudes toward fish; it was less likely to be frequent in households with children age 10 and under present.Consumer/Household Economics,