Single-Particle Self-Excited Oscillator

Electronic feedback is used to self-excite the axial oscillation of a single electron in a Penning trap. Large, stable, easily detected oscillations arise even in an anharmonic potential. Amplitudes are controlled by adjusting the feedback gain, and frequencies can be made nearly independent of amplitude fluctuations. Quantum jump spectroscopy of a perpendicular cyclotron motion reveals the absolute temperature and amplitude of the self-excited oscillation. The possibility to quickly measure parts per billion frequency shifts could open the way to improved measurements of e-, e+, p, and [overline p] magnetic moments

Measurement of spontaneous emission from a two-dimensional photonic band gap defined microcavity at near-infrared wavelengths

An active, photonic band gap-based microcavity emitter in the near infrared is demonstrated. We present direct measurement of the spontaneous emission power and spectrum from a microcavity formed using a two-dimensional photonic band gap structure in a half wavelength thick slab waveguide. The appearance of cavity resonance peaks in the spectrum correspond to the photonic band gap energy. For detuned band gaps, no resonances are observed. For devices with correctly tuned band gaps, a two-time enhancement of the extraction efficiency was demonstrated compared to detuned band gaps and unpatterned material

Multi-vehicle refill scheduling with queueing

© 2017 We consider the problem of refill scheduling for a team of vehicles or robots that must contend for access to a single physical location for refilling. The objective is to minimise time spent in travelling to/from the refill station, and also time lost to queuing (waiting for access). In this paper, we present principled results for this problem in the context of agricultural operations. We first establish that the problem is NP-hard and prove that the maximum number of vehicles that can usefully work together is bounded. We then focus on the design of practical algorithms and present two solutions. The first is an exact algorithm based on dynamic programming that is suitable for small problem instances. The second is an approximate anytime algorithm based on the branch and bound approach that is suitable for large problem instances with many robots. We present simulated results of our algorithms for three classes of agricultural work that cover a range of operations: spot spraying, broadcast spraying and slurry application. We show that the algorithm is reasonably robust to inaccurate prediction of resource utilisation rate, which is difficult to estimate in cases such as spot application of herbicide for weed control, and validate its performance in simulation using realistic scenarios with up to 30 robots

Assessing influence factors on daily ammonia and greenhouse gas concentrations from an open-sided cubicle barn in hot mediterranean climate

Measurement of gas concentrations constitutes basic knowledge for the computation of emissions from livestock buildings. Although it is well known that hot climate conditions increase gas emissions, in the literature the relation between gas concentrations from open barns and animalrelated parameters has not been investigated yet. This study aimed at filling this gap by evaluating daily gas concentrations within an open-sided barn in hot Mediterranean climate. The influence of microclimatic parameters (MC) and cow behavior and barn management (CBBM) were evaluated for ammonia (NH3 ), methane (CH4 ), and carbon dioxide (CO2 ) concentrations. Results showed that both MC and CBBM affected concentrations of NH3 (p < 0.02), CH4 (p < 0.001), and CO2 (p < 0.001). Higher values of NH3 concentration were detected during the cleaning of the floor by a tractor with scraper, whereas the lowest NH3 concentrations were recorded during animal lying behavior. Measured values of CO2 and CH4 were highly correlated (C = 0.87–0.89) due to the same sources of production (i.e., digestion and respiration). The different management of the cooling systems during the two observation periods reduced significantly CH4 concentrations in the barn when the cooling system in the feeding area was switched off. Based on methodological choices due to the specific barn typology, parameters related to animals can provide information on the variation of gas concentrations in the barn environment in hot climate conditions

Environmental productivity index GIS-based model to estimate prickly pear biomass potential availability for biogas production

Nowadays, climate change is the environmental issue facing the world. To reach the 2030 European Union goals, recently, biogas production through anaerobic digestion has developed significantly, by using alternative biomass sources due to the competition between food and no-food products. In this regard, Opuntia ficus-indica (OFI) has been suggested as a suitable new biomass for producing biomethane within the context of circular economy. In this study, a predictive methodology was applied by combining the Nobel model of environmental productivity index (EPI) and geographic information system (GIS), with the aim of estimating OFI biomass amount, as well as biogas and electricity potential production. The GIS analyses allowed the identification of the most suitable territorial areas for producing biogas from OFI, and an estimation of electricity production. The achieved results are highly valuable information for strategic planning of biogas sector development and could be relevant to the intervention priorities established by the EU

Cross Sectional and Longitudinal Fuzzy Clustering of the NUTS and Positioning of the Italian Regions with Respect to the Regional Competitiveness Index (RCI) Indicators with Contiguity Constraints

In socio-economical clustering often the empirical information is represented by time-varying data generated by indicators observed over time on a set of subnational (regional) units. Usually among these units may exist contiguity relations, spatial but not only.In this paper we propose a fuzzy clustering model of multivariate time-varying data, the longitudinal fuzzy C-Medoids clustering with contiguity constraints. The temporal aspect is dealt with by using appropriate measures of dissimilarity between time trajectories. The contiguity among units is dealt with adding a contiguity matrix as a penalization term in the clustering model.The cross sectional fuzzy C-Medoids clustering with contiguity constraints is obtained considering one instant of time. The model is applied to the classification of the European NUTS on the basis of the observed dynamics of the Basic, Efficiency and Innovation subindexes of the Regional Competitiveness Index (RCI) 2013 and 2016. The positioning of the Italian regions is analyzed through the values of the medoids of the clusters and shows the peculiarities of the regions with respect to the subindexes either in single times or in the dynamic. Two contiguity constraints, one based on the European Western, Southern, Central and Northern geographic areas and one on the level of GDP—taken into account in the computation of the RCI—are also introduced in the models

Entropy-based fuzzy clustering of interval-valued time series

This paper proposes a fuzzy C-medoids-based clustering method with entropy regularization to solve the issue of grouping complex data as interval-valued time series. The dual nature of the data, that are both time-varying and interval-valued, needs to be considered and embedded into clustering techniques. In this work, a new dissimilarity measure, based on Dynamic Time Warping, is proposed. The performance of the new clustering procedure is evaluated through a simulation study and an application to financial time series

The activation of non-linear optical response in Ag@ZnO nanocolloids under an external highly intense electric field

An extensive theoretical and experimental study of the non-linear optical properties of bare and silver-decorated zinc oxide (ZnO and Ag@ZnO) nanostructures, prepared by laser-generated plasmas in water and in water/polyvinyl alcohol (PVA) solutions, is reported. The z-scan technique was used to monitor the activation of the non-linear optical mechanisms, focusing an intense laser radiation through the nanocolloids under study. A classical formalism was adopted to explain the z-scan data of these anisotropic materials and to describe the influence of radiation torque and forces on the optically activated nanostructures. This modelling approach includes effects of nanoparticles rearrangements, also taking into account plasmonic effects. An interesting coupling between the nature of the optical limiting response and the nanostructures reorganization under the high-power laser excitation, used during the z-scan measurements, was found and, for the first time to our knowledge, was explained using a classical theoretical approach