A mapping approach to synchronization in the "Zajfman trap". II: the observed bunch

We extend a recently introduced mapping model, which explains the bunching phenomenon in an ion beam resonator for two ions [Geyer, Tannor, J. Phys. B 37 (2004) 73], to describe the dynamics of the whole ion bunch. We calculate the time delay of the ions from a model of the bunch geometry and find that the bunch takes on a spherical form at the turning points in the electrostatic mirrors. From this condition we derive how the observed bunch length depends on the experimental parameters. We give an interpretation of the criteria for the existence of the bunch, which were derived from the experimental observations by Pedersen et al [Pedersen etal, Phys. Rev. A 65 042704].Comment: 25 pages, 6 figures; added new section 5 and clarified text; submitted to J. Phys.

Centralized calibration of power system dynamic models using variational data assimilation

This paper presents a novel centralized, variational data assimilation approach for calibrating transient dynamic models in electrical power systems, focusing on load model parameters. With the increasing importance of inverter-based resources, assessing power systems' dynamic performance under disturbances has become challenging, necessitating robust model calibration methods. The proposed approach expands on previous Bayesian frameworks by establishing a posterior distribution of parameters using an approximation around the maximum a posteriori value. We illustrate the efficacy of our method by generating events of varying intensity, highlighting its ability to capture the systems' evolution accurately and with associated uncertainty estimates. This research improves the precision of dynamic performance assessments in modern power systems, with potential applications in managing uncertainties and optimizing system operations.Comment: 9 pages, 8 figures, and 1 tabl

The JADE code: Coupling secular exoplanetary dynamics and photo-evaporation

Close-in planets evolve under extreme conditions, raising questions about their origins and current nature. Two predominant mechanisms are orbital migration, which brings them close to their star, and atmospheric escape under the resulting increased irradiation. Yet, their relative roles remain unclear because we lack models that couple the two mechanisms with high precision on secular timescales. To address this need, we developed the JADE code, which simulates the secular atmospheric and dynamical evolution of a planet around its star, and can include the perturbation induced by a distant third body. On the dynamical side, the 3D evolution of the orbit is modeled under stellar and planetary tidal forces, a relativistic correction, and the action of the distant perturber. On the atmospheric side, the vertical structure of the atmosphere is integrated over time based on its thermodynamical properties, inner heating, and the evolving stellar irradiation, which results, in particular, in photo-evaporation. The JADE code is benchmarked on GJ436 b, prototype of evaporating giants on eccentric, misaligned orbits at the edge of the hot Neptunes desert. We confirm that its orbital architecture is well explained by Kozai migration and unveil a strong interplay between its atmospheric and orbital evolution. During the resonance phase, the atmosphere pulsates in tune with the Kozai cycles, which leads to stronger tides and an earlier migration. This triggers a strong evaporation several Gyr after the planet formed, refining the paradigm that mass loss is dominant in the early age of close-in planets. This suggests that the edge of the desert could be formed of warm Neptunes whose evaporation was delayed by migration. It strengthens the importance of coupling atmospheric and dynamical evolution over secular timescales, which the JADE code will allow simulating for a wide range of systems.Comment: 20 pages, 2 figures, accepted in A&

The effects of calcite silicon-mediated particle film application on leaf temperature and grape composition of Merlot (Vitis vinifera L.) vines under different irrigation conditions

This study examined whether the application of calcite-silicon mediated particle film (CaPF) at veraison can mitigate a drought-induced increase in leaf temperature on grapevine, thus contributing to improved leaf functionality, yield and grape composition traits. A total of 48 five-year-old Merlot (Vitis vinifera L.) vines grafted onto SO4 were grown (in 20 L PVC pots) under Mediterranean conditions (Southern Italy). The vines were pruned to two spurs with two winter buds irrigated daily to 100 % field capacity, and fertilised weekly. At veraison and using a 2×2 factorial experimental design, the two main factors, thermoregulation and water, were imposed at two levels: spraying with a thermoregulation compound (CaPF) and no spraying (NS); irrigation (WW) and drought stress (D)). A group of 24 vines was subjected to a 15-day drought period by receiving, every day, 25 % (D) of the daily water consumption of WW vines. The other 24 vines continued to be fully irrigated on a daily basis (WW). Twelve vines per group were sprayed (WW+CaPF, D+CaPF) with calcite-silicon mediate (3 % V/V) at the beginning of drought imposition, the remaining 24 vines were not sprayed (WW-NS, D-NS). Soil water moisture and stem water potential values were monitored from 11.30 to 13:30 nearly every week, and other vegetative and reproductive parameters were also measured. During the experiment, air temperature peaked at ≈35 °C at midday, VPD at about 3.7 kPa and PAR reached ≈2000 µmol m-2 s–1. Results show that in CaPF sprayed vines, leaf-air temperature differences were lower than in unsprayed vines in both irrigated and drought stressed groups. WW+CaPF vines retained significantly more leaf area and showed the highest value of accumulated vine transpiration. Calcite-silicon mediated particle film could enhance the resilience of grapevine to adverse environmental conditions and may contribute to preserve terroir elements in highly reputed wine grape growing areas. The study showed that foliar application of calcite silicon-mediated processed particles films can be used in arid regions to mitigate leaf temperatures in grapevines

Egypt’s Exchange Rate Regime Policy after the Float

The major purpose of this paper is to analyze the actual exchange rate policies followed by Egypt since the Central Bank of Egypt (CBE) announced its adoption of a floating ER regime in January 2003. Based on our analytical and empirical approaches to analyzing the actual degree of flexibility of exchange rate policies we concluded the following. First, the de jure “Free Floating” ER Regime that the CBE announced in January, 2003 was not preserved during the period of the study. Second, the changes in the IMF’s de facto classifications of Egypt’s actual exchange rate policies were broadly accurate. Third, the move from light to heavy exchange market management in 2011 leads to what has been called a one way speculative option. Fourth, too much attention has been paid to the US dollar in setting exchange rate policies. Since the dollar exchange rate sometimes moves substantially against some of these other currencies such as the Euro, it is important that such fluctuations should also be taken into account.

Is dietary zinc protective for type 2 diabetes? Results from the Australian longitudinal study on women's health

Background: Animal studies have shown that zinc intake has protective effects against type 2 diabetes, but few studies have been conducted to examine this relationship in humans. The aim of this study is to investigate if dietary zinc is associated with risk of type 2 diabetes in a longitudinal study of mid-age Australian women. Methods: Data were collected from a cohort of women aged 45-50 years at baseline, participating in the Australian Longitudinal Study on Women's Health. A validated food frequency questionnaire was used to assess dietary intake and other nutrients. Predictors of 6-year incidence of type 2 diabetes were examined using multivariable logistic regression. Results: From 8921 participants, 333 incident cases of type 2 diabetes were identified over 6 years of follow-up. After adjustment for dietary and non-dietary factors, the highest quintile dietary zinc intake had almost half the odds of developing type 2 diabetes (OR = 0.50, 95% C.I. 0.32-0.77) compared with the lowest quintile. Similar findings were observed for the zinc/iron ratio; the highest quintile had half the odds of developing type 2 diabetes (OR = 0.50, 95% C.I 0.30-0.83) after multivariable adjustment of covariates. Conclusions: Higher total dietary zinc intake and high zinc/iron ratio are associated with lower risk of type 2 diabetes in women. This finding is a positive step towards further research to determine if zinc supplementation may reduce the risk of developing type 2 diabetes. © 2013 Vashum et al.; licensee BioMed Central Ltd

Closed-loop optimization of fast-charging protocols for batteries with machine learning.

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines1,2. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years3-5. Furthermore, both large parameter spaces and high sampling variability3,6,7 necessitate a large number of experiments. Hence, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology  to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users8,9. We combine two key elements to reduce the optimization cost: an early-prediction model5, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm10,11, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces