Magnetic helicity fluxes and their effect on stellar dynamos

Magnetic helicity fluxes in turbulently driven alpha^2 dynamos are studied to demonstrate their ability to alleviate catastrophic quenching. A one-dimensional mean-field formalism is used to achieve magnetic Reynolds numbers of the order of 10^5. We study both diffusive magnetic helicity fluxes through the mid-plane as well as those resulting from the recently proposed alternate dynamic quenching formalism. By adding shear we make a parameter scan for the critical values of the shear and forcing parameters for which dynamo action occurs. For this $\alpha\Omega$ dynamo we find that the preferred mode is antisymmetric about the mid-plane. This is also verified in 3-D direct numerical simulations.Comment: 5 pages, 6 figures, proceedings of IAU Symp. 286, Comparative Magnetic Minima: characterizing quiet times in the Sun and star

Dynamic Currency Conversion and Consumer Protection: Finding the right rules. ECRI Commentary No. 22, 19 March 2018

Several policy options are under discussion for better regulation of the dynamic currency conversion (DCC) payment service, each of which offers specific advantages but also poses distinct challenges. Enhancing transparency, for example, will require creative solutions. The imposition of fixed price caps would call for the design of robust criteria to determine the level of the caps. And the adjustment of the payment card chip would necessitate the adoption of common standards between card providers. From a consumer protection perspective, a ban on DCC makes sense only if all other options have been exhausted and if consumers can find satisfactory alternatives. Overall, despite the challenges it presents, the first option – enhancing transparency – is the most promising. The mandatory disclosure of an indicative spread seems to be the best way for most consumers to truly understand what is at stake and how much they are paying for what

Coarse Graining Makes It Hard to See Micro-Macro Entanglement

Observing quantum effects such as superpositions and entanglement in macroscopic systems requires not only a system that is well protected against environmental decoherence, but also sufficient measurement precision. Motivated by recent experiments, we study the effects of coarse-graining in photon number measurements on the observability of micro-macro entanglement that is created by greatly amplifying one photon from an entangled pair. We compare the results obtained for a unitary quantum cloner, which generates micro-macro entanglement, and for a measure-and-prepare cloner, which produces a separable micro-macro state. We show that the distance between the probability distributions of results for the two cloners approaches zero for a fixed moderate amount of coarse-graining. Proving the presence of micro-macro entanglement therefore becomes progressively harder as the system size increases.Comment: 5 pages, 3 figure

Supplier development practice: arising the problems of upstream delivery for a food distribution SME in the UK

The paper aims to emphasize on the impacts of the supplier development on reducing the defects in supplier quality for a food distribution small–medium sized enterprise (SME). An empirical study was conducted to measure the performance of the suppliers in three different key performance indicators of the outsourcing and supplier’s performance to arise the existing problems via information exchange, data collection and data analysis. It was found that supplier development through data and information exchange and better communication by any food distribution SME raises the problems more promptly. This can dramatically change the supplier’s behavior to improve the quality of the supplier’s service and products. It is suggested that more research is required to raise other key performance indicators and their related problems and to develop more improvement practices. Six sigma methodologies could be the potential good practices to be focused in future research studies. Supplier performance measurement, which encompasses data exchange and data collection, develops the systematic flow of information, which potentially improves the flow of goods and the whole food supply chain to address the final consumer satisfaction. The research took a novel approach in adopting some transport related key performance indicators of the food supply to the food distribution and retailing sector, which is almost a new approach in food industry

Cooperative and synchronized rotation in motorized porous frameworks:Impact on local and global transport properties of confined fluids

Molecules in gas and liquid states, as well as in solution, exhibit significant and random Brownian motion. Molecules in the solid-state, although strongly immobilized, can still exhibit significant intramolecular dynamics. However, in most framework materials, these intramolecular dynamics are driven by temperature, and therefore are neither controlled nor spatially or temporarily aligned. In recent years, several examples of molecular machines that allow for a stimuli-responsive control of dynamical motion, such as rotation, have been reported. In this contribution, we investigate the local and global properties of a Lennard-Jones (LJ) fluid surrounding a molecular motor and consider the influence of cooperative and non-directional rotation for a molecular motor-containing pore system. This study uses classical molecular dynamics simulations to describe a minimal model, which was developed to resemble known molecular motors. The properties of an LJ liquid surrounding an isolated molecular motor remain mostly unaffected by the introduced rotation. We then considered an arrangement of motors within a one-dimensional pore. Changes in diffusivity for pore sizes approaching the length of the rotor were observed, resulting from rotation of the motors. We also considered the influence of cooperative motor directionality on the directional transport properties of this confined fluid. Importantly, we discovered that specific unidirectional rotation of altitudinal motors can produce directed diffusion. This study provides an essential insight into molecular machine-containing frameworks, highlighting the specific structural arrangements that can produce directional mass transport

Determination of tomato quality attributes using portable NIR-sensors

As part of a research project a multidisciplinary approach of different research institutes is followed to investigate the possibility of using a commercially available miniaturized NIR-sensor for the determination of tomato fruit quality parameters in postharvest. Correlation of spectra and tomato reference values of firmness, dry matter and total soluble solids showed good prediction accuracy. Additionally the decline of firmness over storage time with respect to storage temperature of tomatoes could be modelled. Therefore, the decline of firmness as an indicator for shelf-life can be predicted using this portable NIR-Sensor

PopSkipJump: Decision-Based Attack for Probabilistic Classifiers

Most current classifiers are vulnerable to adversarial examples, small input perturbations that change the classification output. Many existing attack algorithms cover various settings, from white-box to black-box classifiers, but typically assume that the answers are deterministic and often fail when they are not. We therefore propose a new adversarial decision-based attack specifically designed for classifiers with probabilistic outputs. It is based on the HopSkipJump attack by Chen et al. (2019, arXiv:1904.02144v5 ), a strong and query efficient decision-based attack originally designed for deterministic classifiers. Our P(robabilisticH)opSkipJump attack adapts its amount of queries to maintain HopSkipJump's original output quality across various noise levels, while converging to its query efficiency as the noise level decreases. We test our attack on various noise models, including state-of-the-art off-the-shelf randomized defenses, and show that they offer almost no extra robustness to decision-based attacks. Code is available at https://github.com/cjsg/PopSkipJump .Comment: ICML'21. Code available at https://github.com/cjsg/PopSkipJump . 9 pages & 7 figures in main part, 14 pages & 10 figures in appendi

Noise Regularization for Conditional Density Estimation

Modelling statistical relationships beyond the conditional mean is crucial in many settings. Conditional density estimation (CDE) aims to learn the full conditional probability density from data. Though highly expressive, neural network based CDE models can suffer from severe over-fitting when trained with the maximum likelihood objective. Due to the inherent structure of such models, classical regularization approaches in the parameter space are rendered ineffective. To address this issue, we develop a model-agnostic noise regularization method for CDE that adds random perturbations to the data during training. We demonstrate that the proposed approach corresponds to a smoothness regularization and prove its asymptotic consistency. In our experiments, noise regularization significantly and consistently outperforms other regularization methods across seven data sets and three CDE models. The effectiveness of noise regularization makes neural network based CDE the preferable method over previous non- and semi-parametric approaches, even when training data is scarce