J.M. Burgerscentrum

Accurate estimation of thermosphere mass density and horizontal winds from satellite accelerometer measurements is crucial for understanding the environment experienced by low-Earth-orbit satellites. A critical step in this process is removing non-aerodynamic forces, such as radiation pressure, from calibrated accelerometer data. However, uncertainties in surface reflection and absorption coefficients, as well as incomplete thermal property information and calibration parameters for the accelerometer, often limit the accuracy of modeling. Therefore, this study presents a method for jointly optimizing radiation pressure parameters and accelerometer scale factors in the cross-track and radial direction and demonstrates their impact on wind observations.During initial studies, the acceleration residuals (the difference between modeled and measured acceleration) in the cross-track direction exhibited a geographical pattern correlated with the magnetic field for both GRACE-A and GRACE-B. However, the residual is opposite in sign for both satellites in the orbital frame. As the satellites are in nearly the same orbit, with an along-track distance separation of only approximately 220km, this cannot be attributed to a vector-based force. The root cause has not yet been identified but could possibly be attributed to an instrument issue. However, it can be empirically corrected in the cross-track accelerometer measurements using quadratic functions of the magnetic vector components.To isolate radiation pressure as much as possible during the optimization, we use GRACE data from 2009, a period when radiation pressure dominated over aerodynamic drag due to the low solar activity. Following the optimization, a significant reduction in residuals was observed for both GRACE-A and GRACE-B, despite the coefficients being tuned using only GRACE-A data. Including the magnetic correction increased consistency between GRACE-A and GRACE-B. Overall, the method achieved RMS reductions in unmodeled accelerations of more than 13% in the cross-track direction and 32% in the radial direction, indicating improved accuracy of the radiation pressure model.Using the proposed radiation pressure model, we demonstrated increased consistency in observed crosswinds between GRACE-A and GRACE-B during periods of higher thermosphere mass density. The proposed approach is generalizable to future missions and improves neutral density and crosswind estimation from precise accelerometer measurements, thereby supporting space weather monitoring and forecasting efforts in the thermosphere.

Failure analysis is a collective steps and procedures used to discover the root cause of a failed semiconductor integrated circuit (IC). Amongst the many challenges faced during failure analysis, 2 challenges will be highlighted as the objectives in this study. The first is to preserve the Nickel-plating layer on the lead finger during sample preparation for repackaging process. The current methods of using acid or laser tend to damage this layer which later hinders the ability for wire bonding during repackaging. For the second, the copper wires in a stacked-die IC tend to be damaged during Film Over Wire (FOW) removal with acid etching which causes the IC to fail electrical tests and disrupts the whole failure analysis work flow. With the methodology of using the Microwave Induced Plasma (MIP) system, the desired outcomes for both objectives could be produced with the predefined setting in the system which uses the mixture of oxygen and argon gas to form a plasma effluent that can selectively remove organic materials such as mold compound filler and polymeric materials but remains the inorganic materials such as metals. The novelty in this study is seen in the ability of the MIP to expose the lead fingers while preserving the condition of the Ni-plating layer for repackaging purpose and also seen in the ability to remove the FOW material completely while maintaining the copper wires connectivity in a stacked-die ICs. By achieving the 2 objectives, failure analysis can be continued without any obstacles and the root cause of the failures can be effectively addressed.

Abstract. Models used in wind resource assessment (WRA) range from engineering wake models and computational fluid dynamics models to mesoscale weather models with wind farm parameterizations and, more recently, large-eddy simulation (LES). The latter two produce time series of wind farm power of a certain period. This simulation period is, in the case of LES, mostly limited to ≤ 1 year due to the computational costs. However, estimates of long-term (O(10 years)) power production are of high value to many parties involved in WRA. To address the need to calculate long-term annual energy production from ≤ 1-year model runs, therefore, this paper presents methods to estimate the long-term (O(10 years)) power production of a wind farm using a ≤ 1-year simulation. To validate the methods, a 10-year LES of a hypothetical large offshore wind farm is performed. The methods work by estimating the conditional probability densities between wind farm power from the LES and wind speed from reanalysis data (ERA5) from a short (≤ 1 year) LES run. The conditional probability densities are then integrated over 10 years of ERA5 wind speed, yielding an estimate of the long-term mean power production. This “long-term correction” method is validated on varying simulation periods, selected with four different day-selection techniques. When applied to a simulation period of 365 consecutive days, the methods can estimate the 10-year mean power production with a mean absolute error of around 0.35 % of the long-term mean. When choosing the simulation period with day-selection techniques that represent the long-term climate, only roughly 200 simulation days are needed to achieve the same accuracy. Finally, a method to also include wind observations in the long-term correction is presented and tested. This requires an additional “free stream” LES run without active turbines and gives estimates of long-term power and wind that are corrected for a potential LES bias. Although validation of this final approach is difficult in the employed modeling strategy, it gives valuable insights and fits within the common WRA practice of combining models and observations. The presented techniques are based on physical arguments, computationally cheap, and simple to implement. Furthermore, they are not limited to LES but can be applied to other time-series-based models. As such, they could be a useful extension for the diverse set of modeling, observational, and statistical techniques used in WRA.

Accurately estimating sea state parameters is crucial for ship safety and efficiency. The objective of this paper is to study the applicability of the Adaptive Kalman filter (AKF) to estimate sea state parameters—significant wave height, peak period, and relative mean wave direction—using onboard ship motion measurements. The main idea is to assess the performance of this method under real-world conditions including varying ship forward speed and heading and noisy measurements. In this study, data recorded from onboard the United States Coast Guard Cutter (USCGC) STRATTON is considered for testing the method. The method's performance is evaluated by comparing the estimated sea state parameters to those obtained from the Copernicus hind cast model. The obtained results show the AKF's capacity to estimate sea state parameters under real-world conditions, such as variable forward speeds and potential sensor and model inaccuracies.

Self-awareness has most commonly been studied in nonhuman animals by implementing mirror self-recognition (MSR) tasks. The validity of such tasks as a stand-alone method has, however, been debated due to their high interindividual variation (including in species deemed self-aware like chimpanzees), their reliance on only one sensory modality, their discrete outcomes (i.e., pass/fail) and, in general, questionned regarding their ability to assess self-awareness. Therefore, a greater variety of methods that assess different aspects of the self, while simultaneously contributing to a more gradualist view of self-awareness, would be desirable. One such method is the body-as-obstacle task (BAO), testing for another dimension of body self-awareness. The ability to understand one's own body as an obstacle to the completion of a desired action emerges in young children at approximately the same age as mirror self-recognition, suggesting a shared mental representation. Whereas recently some studies showed body self-awareness in nonhuman animals, so far, outside of children no studies have compared how the performances of individuals relate between these two tasks. Therefore, here we study both a MSR and a BAO task in chimpanzees and gorillas. We chose these species particularly because evidence for MSR in chimpanzees is well established, whereas results for gorillas have been mixed, which has been attributed to the study design of MSR tasks, and for which a BAO task might thus provide more conclusive evidence. We find that although only some chimpanzees showed evidence for mirror self-recognition, thus replicating previous findings on interspecies differences in MSR, chimpanzees and gorillas performed equally well in the BAO task. Yet, we further found no correlation between the individuals' performances in both tasks. We discuss the implications of these findings for the interpretation of the results of BAO tasks as a possible alternative paradigm for the study of self-awareness in non-human animals.

Living organisms control the formation of mineral skeletons and other structures through biomineralization. Major phylogenetic groups usually consistently follow a single biomineralization pathway. Foraminifera, which are very efficient marine calcifiers, making a substantial contribution to global carbonate production and global carbon sequestration, are regarded as an exception. This phylum has been commonly thought to follow two contrasting models of either in situ 'mineralization of extracellular matrix' attributed to hyaline rotaliid shells, or 'mineralization within intracellular vesicles' attributed to porcelaneous miliolid shells. Our previous results on rotaliids along with those on miliolids in this paper question such a wide divergence of biomineralization pathways within the same phylum of Foraminifera. We have found under a high-resolution scanning electron microscopy (SEM) that precipitation of high-Mg calcitic mesocrystals in porcelaneous shells takes place in situ and form a dense, chaotic meshwork of needle-like crystallites. We have not observed calcified needles that already precipitated in the transported vesicles, what challenges the previous model of miliolid mineralization. Hence, Foraminifera probably utilize less divergent calcification pathways, following the recently discovered biomineralization principles. Mesocrystalline chamber walls in both models are therefore most likely created by intravesicular accumulation of pre-formed liquid amorphous mineral phase deposited and crystallized within the extracellular organic matrix enclosed in a biologically controlled privileged space by active pseudopodial structures. Both calcification pathways evolved independently in the Paleozoic and are well conserved in two clades that represent different chamber formation modes.

This letter ``H'' is written in turbulent air by tagging molecules in the focus of intense laser beams that cross in space. In the course of 40 microseconds, turbulence deforms and disperses the pattern. It could be used as a way to measure the velocity of the turbulent eddies. However, more importantly, it reveals the intricate interplay between molecular diffusion and turbulent dispersion.

Abstract Living organisms control the formation of mineral skeletons and other structures through biomineralization. Major phylogenetic groups usually consistently follow a single biomineralization pathway. Foraminifera, which are very efficient marine calcifiers, making a substantial contribution to global carbonate production and global carbon sequestration, are regarded as an exception. This phylum has been commonly thought to follow two contrasting models of eitherin situ“mineralization of extracellular matrix” attributed to hyaline rotaliid shells, or “mineralization within intracellular vesicles” attributed to porcelaneous miliolid shells. Our previous results on rotaliids along with those on miliolids in this paper question such a wide divergence of biomineralization pathways within the same phylum of Foraminifera. We found that both groups produced calcareous shells via the intravesicular formation of unstable mineral precursors (Mg-rich amorphous calcium carbonates) supplied by endocytosed seawater and deposited at the site of new wall formation within the organic matrix. Precipitation of high-Mg calcitic mesocrystals took placein situand formed a dense, chaotic meshwork of needle-like crystallites. We did not observe deposition of calcified needles that had already precipitated in the transported vesicles, which challenges the previous model of miliolid mineralization. Hence, Foraminifera utilize less divergent calcification pathways, following the recently discovered biomineralization principles. Mesocrystalline chamber walls are therefore apparently created by accumulating and assembling particles of pre-formed liquid amorphous mineral phase within the extracellular organic matrix enclosed in a biologically controlled privileged space by active pseudopodial structures. Both calcification pathways evolved independently in the Paleozoic and are well-conserved in two clades that represent different chamber formation modes.