A multi-objective extremal optimisation approach applied to RFID antenna design

Extremal Optimisation (EO) is a recent nature-inspired meta-heuristic whose search method is especially suitable to solve combinatorial optimisation problems. This paper presents the implementation of a multi-objective version of EO to solve the real-world Radio Frequency IDentification (RFID) antenna design problem, which must maximise efficiency and minimise resonant frequency. The approach we take produces novel modified meander line antenna designs. Another important contribution of this work is the incorporation of an inseparable fitness evaluation technique to perform the fitness evaluation of the components of solutions. This is due to the use of the NEC evaluation suite, which works as a black box process. When the results are compared with those generated by previous implementations based on Ant Colony Optimisation (ACO) and Differential Evolution (DE), it is evident that our approach is able to obtain competitive results, especially in the generation of antennas with high efficiency. These results indicate that our approach is able to perform well on this problem; however, these results can still be improved, as demonstrated through a manual local search process.Full Tex

An optimal gains matrix for time-delay feedback control

In this paper we propose an optimal time-delayed feedback control (TDFC) for tracking unstable periodic orbits (UPOs). It is shown that TDFC will drive a trajectory onto a periodic orbit while minimising an integral of a cost function of the error in periodicity and the control e®ort. This optimal TDFC relies on the linearisation about the delayed trajectory not the UPO itself and therefore can be implemented without a priori knowledge of a reference orbit. This optimal TDFC is applied to the problem of tracking an unstable periodic orbit in the nonlinear equations describing the circular restricted three-body problem. The results of this investigation demonstrate that TDFC could e±ciently drive a spacecraft onto a periodic orbit in the vicinity of a (UPO) halo orbit

Efficient Emulation of Radiative Transfer Codes Using Gaussian Processes and Application to Land Surface Parameter Inferences

There is an increasing need to consistently combine observations from different sensors to monitor the state of the land surface. In order to achieve this, robust methods based on the inversion of radiative transfer (RT) models can be used to interpret the satellite observations. This typically results in an inverse problem, but a major drawback of these methods is the computational complexity. We introduce the concept of Gaussian Process (GP) emulators: surrogate functions that accurately approximate RT models using a small set of input (e.g., leaf area index, leaf chlorophyll, etc.) and output (e.g., top-of-canopy reflectances or at sensor radiances) pairs. The emulators quantify the uncertainty of their approximation, and provide a fast and easy route to estimating the Jacobian of the original model, enabling the use of e.g., efficient gradient descent methods. We demonstrate the emulation of widely used RT models (PROSAIL and SEMIDISCRETE) and the coupling of vegetation and atmospheric (6S) RT models targetting particular sensor bands. A comparison with the full original model outputs shows that the emulators are a viable option to replace the original model, with negligible bias and discrepancies which are much smaller than the typical uncertainty in the observations. We also extend the theory of GP to cope with models with multivariate outputs (e.g., over the full solar reflective domain), and apply this to the emulation of PROSAIL, coupled 6S and PROSAIL and to the emulation of individual spectral components of 6S. In all cases, emulators successfully predict the full model output as well as accurately predict the gradient of the model calculated by finite differences, and produce speed ups between 10,000 and 50,000 times that of the original model. Finally, we use emulators to invert leaf area index ( L A I ), leaf chlorophyll content ( C a b ) and equivalent leaf water thickness ( C w ) from a time series of observations from Sentinel-2/MSI, Sentinel-3/SLSTR and Proba-V observations. We use sophisticated Hamiltonian Markov Chain Monte Carlo (MCMC) methods that exploit the speed of the emulators as well as the gradient estimation, a variational data assimilation (DA) method that extends the problem with temporal regularisation, and a particle filter using a regularisation model. The variational and particle filter approach appear more successful (meaning parameters closer to the truth, and smaller uncertainties) than the MCMC approach as a result of using the temporal regularisation mode. These work therefore suggests that GP emulators are a practical way to implement sophisticated parameter retrieval schemes in an era of increasing data volumes

The clockfront and wavefront model revisited

The currently accepted interpretation of the clock and wavefront model of somitogenesis is that a posteriorly moving molecular gradient sequentially slows the rate of clock oscillations, resulting in a spatial readout of temporal oscillations. However, while molecular components of the clocks and wavefronts have now been identified in the pre-somitic mesoderm (PSM), there is not yet conclusive evidence demonstrating that the observed molecular wavefronts act to slow clock oscillations. Here we present an alternative formulation of the clock and wavefront model in which oscillator coupling, already known to play a key role in oscillator synchronisation, plays a fundamentally important role in the slowing of oscillations along the anterior–posterior (AP) axis. Our model has three parameters which can be determined, in any given species, by the measurement of three quantities: the clock period in the posterior PSM, somite length and the length of the PSM. A travelling wavefront, which slows oscillations along the AP axis, is an emergent feature of the model. Using the model we predict: (a) the distance between moving stripes of gene expression; (b) the number of moving stripes of gene expression and (c) the oscillator period profile along the AP axis. Predictions regarding the stripe data are verified using existing zebrafish data. We simulate a range of experimental perturbations and demonstrate how the model can be used to unambiguously define a reference frame along the AP axis. Comparing data from zebrafish, chick, mouse and snake, we demonstrate that: (a) variation in patterning profiles is accounted for by a single nondimensional parameter; the ratio of coupling strengths; and (b) the period profile along the AP axis is conserved across species. Thus the model is consistent with the idea that, although the genes involved in pattern propagation in the PSM vary, there is a conserved patterning mechanism across species

A composite K-band Luminosity Function for Cluster Galaxies

We present a composite K-band luminosity function for 10 clusters at low redshift, where member galaxies are identified from an existing spectroscopic survey (the 2dF galaxy redshift survey). Our kinematically selected K-band luminosity function is well fitted by a Schechter function with $M^*_K=-24.50 + 5\log h$ and $\alpha=-0.98$ over $-27 < <M_K -5\log h < -22$. This is very similar to the 2dF field value and suggests that the integrated mass accretion history of galaxies does not vary strongly with environmentComment: 3 pages, 1 figure, Astronomische Nachrichten (JENAM 2008 Symposium 6

In Search of the Edge: A Bayesian Exploration of the Detectability of Red Edges in Exoplanet Reflection Spectra

Reflection spectroscopy holds great promise for characterizing the atmospheres and surfaces of potentially habitable terrestrial exoplanets. The surface of the modern Earth exhibits a sharp albedo change near 750 nm caused by vegetation - the red edge - which would leave a strong spectral signature if present on an exoplanet. However, the retrieval of wavelength-dependent surface properties from reflection spectra has seen relatively little study. Here, we propose a new surface albedo parameterization capable of retrieving the wavelength location of a priori unknown 'edge-like' features. We demonstrate that a wavelength-dependent surface albedo model achieves higher accuracy in retrieving atmospheric composition. Wavelength-dependent surfaces are also generally preferred over a uniform albedo model when retrieving simulated reflection spectra for a modern Earth analog, even for moderate signal-to-noise ratios (S/N = 10) and Earth-like clouds. Further, the location of the modern Earth's red edge can be robustly and precisely constrained (within 70 nm for S/N = 10). Our results suggest that future space-based direct imaging missions have the potential to infer surface compositions for rocky exoplanets, including spectral edges similar to those caused by life on the modern Earth.Comment: 23 pages, 17 figures. Accepted for publication in Ap

Determining Life Cycle Emissions of Hydrogen Production Using the 45VH2-GREET Model for the 45V Hydrogen Production Tax Credit

This study provides an analysis of life cycle greenhouse gas (GHG) emissions associated with hydrogen production pathways in the context of the 45V clean hydrogen production tax credit (45V PTC) under the 2022 Inflation Reduction Act (IRA). The 45V PTC mandates a well-to-gate system boundary for assessing life cycle GHG emissions, focusing on emissions up to the point of hydrogen production, including feedstock-related emissions. Central to this study is the use of the 45VH2-GREET model to determine the well-to-gate life cycle GHG emissions. The study focuses on three hydrogen production pathways: Low-temperature electrolysis (Case 1) Natural gas steam methane reforming (SMR) (Case 2) Natural gas autothermal reforming (ATR) (Case 3) For hydrogen production via low-temperature electrolysis, the study reveals that facilities must source the vast majority of the electricity from zero-carbon sources to qualify for the full $3.00/kgH2 45V PTC value. For hydrogen production via SMR using 100% fossil natural gas (FNG) feedstock, high carbon capture and storage (CCS) rates, at least 82 – 96% depending on electricity source, are key to qualify for any level of the 45V PTC. Although 100% landfill natural gas (LFG) feedstock significantly increases the eligibility range for 45V PTC, some level of CCS technology is still required with CCS rates of at least 34 – 42%, depending on electricity source, to qualify for any level of the 45V PTC. Similarly, for hydrogen production via ATR using 100% FNG feedstock, high CCS rates, at least 80 – 94%, depending on electricity source, are necessary to qualify for any level of the 45V PTC. However, certain regions with high grid carbon intensity (CI) may not be eligible to qualify even with 100% CCS rates. Using 100% LFG feedstock increases the potential to qualify for 45V PTC, but still necessitates some level of CCS technology with at least 6 – 28% CCS, depending on electricity source. Additionally, the analysis considered the use of valorized co-products, specifically oxygen, steam, and nitrogen, to reduce the CI of produced hydrogen, thereby aiding in meeting eligibility requirements for the 45V PTC. This study underscores the importance of integrating zero-carbon electricity (ZCE), implementing CCS technology and co-product valorization, and careful selection of feedstocks to maximize eligibility for the 45V PTC. Additionally, it provides insights into the various limitations of the latest 45V-GREET model, identifying opportunities for future research to further evaluate the model’s fixed assumptions and constraints. The findings are valuable for stakeholders in the hydrogen production industry aiming to leverage the 45V PTC to promote low-carbon hydrogen production.Mechanical Engineerin

The evolution of cluster dwarfs

We summarize the results from analyzing six clusters of galaxies at 0.14 < z < 0.40 observed with the Hubble Space Telescope Advanced Camera for Surveys. We derive deep composite luminosity functions in B,g,V,r,i and z down to an absolute magnitude of -14 +5 log h mag. The luminosity functions are fitted by a single Schechter function with M^*=-19.8,-20.9,-21.9, -22.0,-21.7 and -22.3 i B,g,V.r,i,z respectively and alpha=-1.3 for all bands. The data suggest that the red sequence dominates the luminosity function down to more than 6 mag. below L*, the dwarf spheroidal regime. Hence, at least at z=0.3 the red sequence is well established and galaxies down to dwarf spheroidals are fully assembled within these clusters. We do not detect the faint-end upturn (M > -16) that is observed in lower redshift clusters. If this is real, the faint-end population has originated since z = 0.3.Comment: To be published in Astronomische Nachrichten, proceeding of JENAM 2008 Symposium 6. Includes an.cls classfil

Combining multitemporal optical and SAR data for LAI imputation with BiLSTM network

The Leaf Area Index (LAI) is vital for predicting winter wheat yield. Acquisition of crop conditions via Sentinel-2 remote sensing images can be hindered by persistent clouds, affecting yield predictions. Synthetic Aperture Radar (SAR) provides all-weather imagery, and the ratio between its cross- and co-polarized channels (C-band) shows a high correlation with time series LAI over winter wheat regions. This study evaluates the use of time series Sentinel-1 VH/VV for LAI imputation, aiming to increase spatial-temporal density. We utilize a bidirectional LSTM (BiLSTM) network to impute time series LAI and use half mean squared error for each time step as the loss function. We trained models on data from southern Germany and the North China Plain using only LAI data generated by Sentinel-1 VH/VV and Sentinel-2. Experimental results show BiLSTM outperforms traditional regression methods, capturing nonlinear dynamics between multiple time series. It proves robust in various growing conditions and is effective even with limited Sentinel-2 images. BiLSTM's performance surpasses that of LSTM, particularly over the senescence period. Therefore, BiLSTM can be used to impute LAI with time-series Sentinel-1 VH/VV and Sentinel-2 data, and this method could be applied to other time-series imputation issues