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The quantification of spatial propagation of extreme precipitation events is vital in water resources planning and disaster mitigation. However, quantifying these extreme events has always been challenging as many traditional methods are insufficient to capture the nonlinear interrelationships between extreme event time series. Therefore, it is crucial to develop suitable methods for analyzing the dynamics of extreme events over a river basin with a diverse climate and complicated topography. Over the last decade, complex network analysis emerged as a powerful tool to study the intricate spatiotemporal relationship between many variables in a compact way. In this study, we employ two nonlinear concepts of event synchronization and edit distance to investigate the extreme precipitation pattern in the Ganga river basin. We use the network degree to understand the spatial synchronization pattern of extreme rainfall and identify essential sites in the river basin with respect to potential prediction skills. The study also attempts to quantify the influence of precipitation seasonality and topography on extreme events. The findings of the study reveal that (1) the network degree is decreased in the southwest to northwest direction, (2) the timing of 50th percentile precipitation within a year influences the spatial distribution of degree, (3) the timing is inversely related to elevation, and (4) the lower elevation greatly influences connectivity of the sites. The study highlights that edit distance could be a promising alternative to analyze event-like data by incorporating event time and amplitude and constructing complex networks of climate extremes.
In this study, we model a sequence of a confined and a full eruption, employing the relaxed end state of the confined eruption of a kink-unstable flux rope as the initial condition for the ejective one. The full eruption, a model of a coronal mass ejection, develops as a result of converging motions imposed at the photospheric boundary, which drive flux cancellation. In this process, parts of the positive and negative external flux converge toward the polarity inversion line, reconnect, and cancel each other. Flux of the same amount as the canceled flux transfers to a flux rope, increasing the free magnetic energy of the coronal field. With sustained flux cancellation and the associated progressive weakening of the magnetic tension of the overlying flux, we find that a flux reduction of approximate to 11% initiates the torus instability of the flux rope, which leads to a full eruption. These results demonstrate that a homologous full eruption, following a confined one, can be driven by flux cancellation.
As the use of free electron laser (FEL) sources increases, so do the findings mentioning non-linear phenomena occurring at these experiments, such as saturable absorption, induced transparency and scattering breakdowns. These are well known among the laser community, but are still rarely understood and expected among the X-ray community and to date lack tools and theories to accurately predict the respective experimental parameters and results. We present a simple theoretical framework to access short X-ray pulse induced light- matter interactions which occur at intense short X-ray pulses as available at FEL sources. Our approach allows to investigate effects such as saturable absorption, induced transparency and scattering suppression, stimulated emission, and transmission spectra, while including the density of state influence relevant to soft X-ray spectroscopy in, for example, transition metal complexes or functional materials. This computationally efficient rate model based approach is intuitively adaptable to most solid state sample systems in the soft X-ray spectrum with the potential to be extended for liquid and gas sample systems as well. The feasibility of the model to estimate the named effects and the influence of the density of state is demonstrated using the example of CoPd transition metal systems at the Co edge. We believe this work is an important contribution for the preparation, performance, and understanding of FEL based high intensity and short pulse experiments, especially on functional materials in the soft X-ray spectrum.
A rigorous construction of the supersymmetric path integral associated to a compact spin manifold
(2022)
We give a rigorous construction of the path integral in N = 1/2 supersymmetry as an integral map for differential forms on the loop space of a compact spin manifold. It is defined on the space of differential forms which can be represented by extended iterated integrals in the sense of Chen and Getzler-Jones-Petrack. Via the iterated integral map, we compare our path integral to the non-commutative loop space Chern character of Guneysu and the second author. Our theory provides a rigorous background to various formal proofs of the Atiyah-Singer index theorem for twisted Dirac operators using supersymmetric path integrals, as investigated by Alvarez-Gaume, Atiyah, Bismut and Witten.
We study the diffusive motion of a particle in a subharmonic potential of the form U(x) = |x|( c ) (0 < c < 2) driven by long-range correlated, stationary fractional Gaussian noise xi ( alpha )(t) with 0 < alpha <= 2. In the absence of the potential the particle exhibits free fractional Brownian motion with anomalous diffusion exponent alpha. While for an harmonic external potential the dynamics converges to a Gaussian stationary state, from extensive numerical analysis we here demonstrate that stationary states for shallower than harmonic potentials exist only as long as the relation c > 2(1 - 1/alpha) holds. We analyse the motion in terms of the mean squared displacement and (when it exists) the stationary probability density function. Moreover we discuss analogies of non-stationarity of Levy flights in shallow external potentials.
Flexible all-perovskite tandem photovoltaics open up new opportunities for application compared to rigid devices, yet their performance lags behind. Now, researchers show that molecule-bridged interfaces mitigate charge recombination and crack formation, improving the efficiency and mechanical reliability of flexible devices.
In this study, we present an empirical model of the equatorial electron pitch angle distributions (PADs) in the outer radiation belt based on the full data set collected by the Magnetic Electron Ion Spectrometer (MagEIS) instrument onboard the Van Allen Probes in 2012-2019. The PADs are fitted with a combination of the first, third and fifth sine harmonics. The resulting equation resolves all PAD types found in the outer radiation belt (pancake, flat-top, butterfly and cap PADs) and can be analytically integrated to derive omnidirectional flux. We introduce a two-step modeling procedure that for the first time ensures a continuous dependence on L, magnetic local time and activity, parametrized by the solar wind dynamic pressure. We propose two methods to reconstruct equatorial electron flux using the model. The first approach requires two uni-directional flux observations and is applicable to low-PA data. The second method can be used to reconstruct the full equatorial PADs from a single uni- or omnidirectional measurement at off-equatorial latitudes. The model can be used for converting the long-term data sets of electron fluxes to phase space density in terms of adiabatic invariants, for physics-based modeling in the form of boundary conditions, and for data assimilation purposes.
We develop an encounter-based approach for describing restricted diffusion with a gradient drift toward a partially reactive boundary. For this purpose, we introduce an extension of the Dirichlet-to-Neumann operator and use its eigenbasis to derive a spectral decomposition for the full propagator, i.e. the joint probability density function for the particle position and its boundary local time. This is the central quantity that determines various characteristics of diffusion-influenced reactions such as conventional propagators, survival probability, first-passage time distribution, boundary local time distribution, and reaction rate. As an illustration, we investigate the impact of a constant drift onto the boundary local time for restricted diffusion on an interval. More generally, this approach accesses how external forces may influence the statistics of encounters of a diffusing particle with the reactive boundary.
The addition of nano-Al2O3 has been shown to enhance the breakdown voltage of epoxy resin, but its flashover results appeared with disputation. This work concentrates on the surface charge variation and dc flashover performance of epoxy resin with nano-Al2O3 doping. The dispersion of nano-Al2O3 in epoxy is characterized by scanning electron microscopy (SEM) and atomic force microscopy (AFM). The dc flashover voltages of samples under either positive or negative polarity are measured with a finger-electrode system, and the surface charge variations before and after flashovers were identified from the surface potential mapping. The results evidence that nano-Al2O3 would lead to a 16.9% voltage drop for the negative flashovers and a 6.8% drop for positive cases. It is found that one-time flashover clears most of the accumulated surface charges, regardless of positive or negative. As a result, the ground electrode is neighbored by an equipotential zone enclosed with low-density heterocharges. The equipotential zone tends to be broadened after 20 flashovers. The nano-Al2O3 is noticed as beneficial to downsize the equipotential zone due to its capability on charge migration, which is reasonable to maintain flashover voltage at a high level after multiple flashovers. Hence, nano-Al2O3 plays a significant role in improving epoxy with high resistance to multiple flashovers.
Analysis of electrochemical and liver microsomal transformation products of lasalocid by LC/HRMS
(2022)
Rationale:
Lasalocid (LAS), an ionophore, is used in cattle and poultry farming as feed additive for its antibiotic and growth-promoting properties. Literature on transformation products (TP) resulting from LAS degradation is limited. So far, only hydroxylation is found to occur as the metabolic reaction during the LAS degradation. To investigate potential TPs of LAS, we used electrochemistry (EC) and liver microsome (LM) assays to synthesize TPs, which were identified using liquid chromatography high-resolution mass spectrometry (LC/HRMS).
Methods:
Electrochemically produced TPs were analyzed online by direct coupling of the electrochemical cell to the electrospray ionization (ESI) source of a Sciex Triple-TOF high resolution mass spectrometer. Then, EC-treated LAS solution was collected and analyzed offline using LC/HRMS to confirm stable TPs and improve their annotation with a chemical structure due to informative MS/MS spectra. In a complementary approach, TPs formed by rat and human microsomal incubation were investigated using LC/HRMS. The resulting data were used to investigate LAS modification reactions and elucidate the chemical structure of obtained TPs.
Results:
The online measurements identified a broad variety of TPs, resulting from modification reactions like (de-)hydrogenation, hydration, methylation, oxidation as well as adduct formation with methanol. We consistently observed different ion complexations of LAS and LAS-TPs (Na+; 2Na(+) K+; NaNH4+; KNH4+). Two stable methylated EC-TPs were found, structurally annotated, and assigned to a likely modification reaction. Using LM incubation, seven TPs were formed, mostly by oxidation/hydroxylation. After the identification of LM-TPs as Na+-complexes, we identified LM-TPs as K+-complexes.
Conclusion:
We identified and characterized TPs of LAS using EC- and LM-based methods. Moreover, we found different ion complexes of LAS-based TPs. This knowledge, especially the different ion complexes, may help elucidate the metabolic and environmental degradation pathways of LAS.
Neutrophil granulocytes are essential for the first host defense. After leaving the blood circulation they migrate efficiently towards sites of inflammation. They are guided by chemoattractants released from cells within the inflammatory foci. On a cellular level, directional migration is a consequence of cellular front-rear asymmetry which is induced by the concentration gradient of the chemoattractants. The generation and maintenance of this asymmetry, however, is not yet fully understood. Here we analyzed the paths of chemotacting neutrophils with different stochastic models to gain further insight into the underlying mechanisms. Wildtype chemotacting neutrophils show an anomalous superdiffusive behavior. CXCR2 blockade and TRPC6-knockout cause the tempering of temporal correlations and a reduction of chemotaxis. Importantly, such tempering is found both in vitro and in vivo. These findings indicate that the maintenance of anomalous dynamics is crucial for chemotactic behavior and the search efficiency of neutrophils.
The motility of neutrophils and their ability to sense and to react to chemoattractants in their environment are of central importance for the innate immunity. Neutrophils are guided towards sites of inflammation following the activation of G-protein coupled chemoattractant receptors such as CXCR2 whose signaling strongly depends on the activity of Ca2+ permeable TRPC6 channels. It is the aim of this study to analyze data sets obtained in vitro (murine neutrophils) and in vivo (zebrafish neutrophils) with a stochastic mathematical model to gain deeper insight into the underlying mechanisms. The model is based on the analysis of trajectories of individual neutrophils. Bayesian data analysis, including the covariances of positions for fractional Brownian motion as well as for exponentially and power-law tempered model variants, allows the estimation of parameters and model selection. Our model-based analysis reveals that wildtype neutrophils show pure superdiffusive fractional Brownian motion. This so-called anomalous dynamics is characterized by temporal long-range correlations for the movement into the direction of the chemotactic CXCL1 gradient. Pure superdiffusion is absent vertically to this gradient. This points to an asymmetric 'memory' of the migratory machinery, which is found both in vitro and in vivo. CXCR2 blockade and TRPC6-knockout cause tempering of temporal correlations in the chemotactic gradient. This can be interpreted as a progressive loss of memory, which leads to a marked reduction of chemotaxis and search efficiency of neutrophils. In summary, our findings indicate that spatially differential regulation of anomalous dynamics appears to play a central role in guiding efficient chemotactic behavior.
How does a systematic time-dependence of the diffusion coefficient D(t) affect the ergodic and statistical characteristics of fractional Brownian motion (FBM)? Here, we answer this question via studying the characteristics of a set of standard statistical quantifiers relevant to single-particle-tracking (SPT) experiments. We examine, for instance, how the behavior of the ensemble- and time-averaged mean-squared displacements-denoted as the standard MSD < x(2)(Delta)> and TAMSD <<(delta(2)(Delta))over bar>> quantifiers-of FBM featuring < x(2) (Delta >> = <<(delta(2)(Delta >)over bar>> proportional to Delta(2H) (where H is the Hurst exponent and Delta is the [lag] time) changes in the presence of a power-law deterministically varying diffusivity D-proportional to(t) proportional to t(alpha-1) -germane to the process of scaled Brownian motion (SBM)-determining the strength of fractional Gaussian noise. The resulting compound "scaled-fractional" Brownian motion or FBM-SBM is found to be nonergodic, with < x(2)(Delta >> proportional to Delta(alpha+)(2H)(-1) and <(delta 2(Delta >) over bar > proportional to Delta(2H). We also detect a stalling behavior of the MSDs for very subdiffusive SBM and FBM, when alpha + 2H - 1 < 0. The distribution of particle displacements for FBM-SBM remains Gaussian, as that for the parent processes of FBM and SBM, in the entire region of scaling exponents (0 < alpha < 2 and 0 < H < 1). The FBM-SBM process is aging in a manner similar to SBM. The velocity autocorrelation function (ACF) of particle increments of FBM-SBM exhibits a dip when the parent FBM process is subdiffusive. Both for sub- and superdiffusive FBM contributions to the FBM-SBM process, the SBM exponent affects the long-time decay exponent of the ACF. Applications of the FBM-SBM-amalgamated process to the analysis of SPT data are discussed. A comparative tabulated overview of recent experimental (mainly SPT) and computational datasets amenable for interpretation in terms of FBM-, SBM-, and FBM-SBM-like models of diffusion culminates the presentation. The statistical aspects of the dynamics of a wide range of biological systems is compared in the table, from nanosized beads in living cells, to chromosomal loci, to water diffusion in the brain, and, finally, to patterns of animal movements.
We analyse mobile-immobile transport of particles that switch between the mobile and immobile phases with finite rates. Despite this seemingly simple assumption of Poissonian switching, we unveil a rich transport dynamics including significant transient anomalous diffusion and non-Gaussian displacement distributions. Our discussion is based on experimental parameters for tau proteins in neuronal cells, but the results obtained here are expected to be of relevance for a broad class of processes in complex systems. Specifically, we obtain that, when the mean binding time is significantly longer than the mean mobile time, transient anomalous diffusion is observed at short and intermediate time scales, with a strong dependence on the fraction of initially mobile and immobile particles. We unveil a Laplace distribution of particle displacements at relevant intermediate time scales. For any initial fraction of mobile particles, the respective mean squared displacement (MSD) displays a plateau. Moreover, we demonstrate a short-time cubic time dependence of the MSD for immobile tracers when initially all particles are immobile.
We study the first-arrival (first-hitting) dynamics and efficiency of a one-dimensional random search model performing asymmetric Levy flights by leveraging the Fokker-Planck equation with a delta-sink and an asymmetric space-fractional derivative operator with stable index alpha and asymmetry (skewness) parameter beta.
We find exact analytical results for the probability density of first-arrival times and the search efficiency, and we analyse their behaviour within the limits of short and long times.
We find that when the starting point of the searcher is to the right of the target, random search by Brownian motion is more efficient than Levy flights with beta <= 0 (with a rightward bias) for short initial distances, while for beta>0 (with a leftward bias) Levy flights with alpha -> 1 are more efficient.
When increasing the initial distance of the searcher to the target, Levy flight search (except for alpha=1 with beta=0) is more efficient than the Brownian search. Moreover, the asymmetry in jumps leads to essentially higher efficiency of the Levy search compared to symmetric Levy flights at both short and long distances, and the effect is more pronounced for stable indices alpha close to unity.
HCNO is a molecule of considerable astrochemical interest as a precursor to prebiotic molecules. It is synthesized by preparative pyrolysis and is unstable at room temperature. Here, we investigate its spectroscopy in the soft X-ray regime at the C 1s, N 1s and O 1s edges. All 1s ionization energies are reported and X-ray absorption spectra reveal the transitions from the 1s to the pi* state. Resonant and normal Auger electron spectra for the decay of the core hole states are recorded in a hemispherical analyzer. An assignment of the experimental spectra is provided with the aid of theoretical counterparts. The latter are using a valence configuration interaction representation of the intermediate and final state energies and wavefunctions, the one-center approximation for transition rates and band shapes according to the moment theory. The computed spectra are in very good agreement with the experimental data and most of the relevant bands are assigned. Additionally, we present a simple approach to estimate relative Auger transition rates on the basis of a minimal basis representation of the molecular orbitals. We demonstrate that this provides a qualitatively good and reliable estimate for several signals in the normal and resonant Auger electron spectra which have significantly different intensities in the decay of the three core holes.
Diffusion with stochastic resetting is a paradigm of resetting processes. Standard renewal or master equation approach are typically used to study steady state and other transport properties such as average, mean squared displacement etc.
What remains less explored is the two time point correlation functions whose evaluation is often daunting since it requires the implementation of the exact time dependent probability density functions of the resetting processes which are unknown for most of the problems.
We adopt a different approach that allows us to write a stochastic solution for a single trajectory undergoing resetting.
Moments and the autocorrelation functions between any two times along the trajectory can then be computed directly using the laws of total expectation. Estimation of autocorrelation functions turns out to be pivotal for investigating the ergodic properties of various observables for this canonical model.
In particular, we investigate two observables (i) sample mean which is widely used in economics and (ii) time-averaged-mean-squared-displacement (TAMSD) which is of acute interest in physics.
We find that both diffusion and drift-diffusion processes with resetting are ergodic at the mean level unlike their reset-free counterparts. In contrast, resetting renders ergodicity breaking in the TAMSD while both the stochastic processes are ergodic when resetting is absent. We quantify these behaviors with detailed analytical study and corroborate with extensive numerical simulations.
Our results can be verified in experimental set-ups that can track single particle trajectories and thus have strong implications in understanding the physics of resetting.
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusionmodel and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a wellcalibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output.
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusion model and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a well-calibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output. <br /> Diffusive motions in complex environments such as living biological cells or soft matter systems can be analyzed with single-particle-tracking approaches, where accuracy of output may vary. The authors involve a machine-learning technique for decoding anomalous-diffusion data and provide an uncertainty estimate together with predicted output.
It has been experimentally demonstrated that reaction rates for molecules embedded in microfluidic optical cavities are altered when compared to rates observed under "ordinary" reaction conditions. However, precise mechanisms of how strong coupling of an optical cavity mode to molecular vibrations affects the reactivity and how resonance behavior emerges are still under dispute. In the present work, we approach these mechanistic issues from the perspective of a thermal model reaction, the inversion of ammonia along the umbrella mode, in the presence of a single-cavity mode of varying frequency and coupling strength. A topological analysis of the related cavity Born-Oppenheimer potential energy surface in combination with quantum mechanical and transition state theory rate calculations reveals two quantum effects, leading to decelerated reaction rates in qualitative agreement with experiments: the stiffening of quantized modes perpendicular to the reaction path at the transition state, which reduces the number of thermally accessible reaction channels, and the broadening of the barrier region, which attenuates tunneling. We find these two effects to be very robust in a fluctuating environment, causing statistical variations of potential parameters, such as the barrier height. Furthermore, by solving the time-dependent Schrodinger equation in the vibrational strong coupling regime, we identify a resonance behavior, in qualitative agreement with experimental and earlier theoretical work. The latter manifests as reduced reaction probability when the cavity frequency omega(c) is tuned resonant to a molecular reactant frequency. We find this effect to be based on the dynamical localization of the vibro-polaritonic wavepacket in the reactant well.
Nanostructured silicon and silicon-aluminum compounds are synthesized by a novel synthesis strategy based on spark plasma sintering (SPS) of silicon nanopowder, mesoporous silicon (pSi), and aluminum nanopowder. The interplay of metal-assisted crystallization and inherent porosity is exploited to largely suppress thermal conductivity. Morphology and temperature-dependent thermal conductivity studies allow us to elucidate the impact of porosity and nanostructure on the macroscopic heat transport. Analytic electron microscopy along with quantitative image analysis is applied to characterize the sample morphology in terms of domain size and interpore distance distributions. We demonstrate that nanostructured domains and high porosity can be maintained in densified mesoporous silicon samples. In contrast, strong grain growth is observed for sintered nanopowders under similar sintering conditions. We observe that aluminum agglomerations induce local grain growth, while aluminum diffusion is observed in porous silicon and dispersed nanoparticles. A detailed analysis of the measured thermal conductivity between 300 and 773 K allows us to distinguish the effect of reduced thermal conductivity caused by porosity from the reduction induced by phonon scattering at nanosized domains. With a modified Landauer/Lundstrom approach the relative thermal conductivity and the scattering length are extracted. The relative thermal conductivity confirms the applicability of Kirkpatrick's effective medium theory. The extracted scattering lengths are in excellent agreement with the harmonic mean of log-normal distributed domain sizes and the interpore distances combined by Matthiessen's rule.
The strong chromospheric absorption lines Ca ii H & K are tightly connected to stellar surface magnetic fields. Only for the Sun, spectral activity indices can be related to evolving magnetic features on the solar disk. The Solar Disk-Integrated (SDI) telescope feeds the Potsdam Echelle Polarimetric and Spectroscopic Instrument (PEPSI) of the Large Binocular Telescope (LBT) at Mt. Graham International Observatory, Arizona, U.S.A. We present high-resolution, high-fidelity spectra that were recorded on 184 & 82 days in 2018 & 2019 and derive the Ca ii H & K emission ratio, that is, the S-index. In addition, we compile excess brightness and area indices based on full-disk Ca ii K-line-core filtergrams of the Chromospheric Telescope (ChroTel) at Observatorio del Teide, Tenerife, Spain and full-disk ultraviolet (UV) 1600 angstrom images of the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO). Thus, Sun-as-a-star spectral indices are related to their counterparts derived from resolved images of the solar chromosphere. All indices display signatures of rotational modulation, even during the very low magnetic activity in the minimum of Solar Cycle 24. Bringing together different types of activity indices has the potential to join disparate chromospheric datasets yielding a comprehensive description of chromospheric activity across many solar cycles.
Chinese CSP for the world?
(2022)
For three consecutive five-year plans since 2006, China has worked on building up an internationally competitive CSP industry and value chain. One big milestone in commercializing proprietary Chinese CSP technology was the 2016 demonstration program of 20 commercial-scale projects. China sought to increase and demonstrate capacities for domestic CSP technology development and deployment. At the end of the 13th five-year period, we take stock of the demonstrated progress of the Chinese CSP industry towards delivering internationally competitive CSP projects. We find that in January 2021, eight commercial-scale projects, in total 500 MW, have been completed and three others were under construction in China. In addition, Chinese EPC’s have participated in three international CSP projects, although proprietary Chinese CSP designs have not been applied outside China. The largest progress has been made in molten-salt tower technology, with several projects by different companies completed and operating successfully: here, the aims were met, and Chinese companies are now at the global forefront of this segment. Further efforts for large-scale demonstration are needed, however, for other CSP technologies, including parabolic trough - with additional demonstration hindered by a lack of further deployment policies. In the near future, Chinese companies seek to employ the demonstrated capabilities in the tower segment abroad and are developing projects using Chinese technology, financing, and components in several overseas markets. If successful, this will likely lead to increasing competition and further cost reductions for the global CSP sector.
The field of movement ecology has seen a rapid increase in high-resolution data in recent years, leading to the development of numerous statistical and numerical methods to analyse relocation trajectories. Data are often collected at the level of the individual and for long periods that may encompass a range of behaviours.
Here, we use the power spectral density (PSD) to characterise the random movement patterns of a black-winged kite (Elanus caeruleus) and a white stork (Ciconia ciconia). The tracks are first segmented and clustered into different behaviours (movement modes), and for each mode we measure the PSD and the ageing properties of the process.
For the foraging kite we find 1/f noise, previously reported in ecological systems mainly in the context of population dynamics, but not for movement data. We further suggest plausible models for each of the behavioural modes by comparing both the measured PSD exponents and the distribution of the single-trajectory PSD to known theoretical results and simulations.
Climate Benefits of Cleaner Energy Transitions in East and South Asia Through Black Carbon Reduction
(2022)
The state of air pollution has historically been tightly linked to how we produce and use energy. Air pollutant emissions over Asia are now changing rapidly due to cleaner energy transitions; however, magnitudes of benefits for climate and air quality remain poorly quantified. The associated risks involve adverse health impacts, reduced agricultural yields, reduced freshwater availability, contributions to climate change, and economic costs. We focus particularly on climate benefits of energy transitions by making first-time use of two decades of high quality observations of atmospheric loading of light-absorbing black carbon (BC) over Kanpur (South Asia) and Beijing (East Asia) and relating these observations to changing energy, emissions, and economic trends in India and China. Our analysis reveals that absorption aerosol optical depth (AAOD) due to BC has decreased substantially, by 40% over Kanpur and 60% over Beijing between 2001 and 2017, and thus became decoupled from regional economic growth. Furthermore, the resultant decrease in BC emissions and BC AAOD over Asia is regionally coherent and occurs primarily due to transitions into cleaner energies (both renewables and fossil fuels) and not due to the decrease in primary energy supply or decrease in use of fossil use and biofuels and waste. Model simulations show that BC aerosols alone contribute about half of the surface temperature change (warming) of the total forcing due to greenhouse gases, natural and internal variability, and aerosols, thus clearly revealing the climate benefits due to a reduction in BC emissions, which would significantly reduce global warming. However, this modeling study excludes responses from natural variability, circulation, and sea ice responses, which cause relatively strong temperature fluctuations that may mask signals from BC aerosols. Our findings show additional benefits for climate (beyond benefits of CO2 reduction) and for several other issues of sustainability over South and East Asia, provide motivation for ongoing cleaner energy production, and consumption transitions, especially when they are associated with reduced emissions of air pollutants. Such an analysis connecting the trends in energy transitions and aerosol absorption loading, unavailable so far, is crucial for simulating the aerosol climate impacts over Asia which is quite uncertain.
Anomalous diffusion with a power-law time dependence vertical bar R vertical bar(2)(t) similar or equal to t(alpha i) of the mean squared displacement occurs quite ubiquitously in numerous complex systems. Often, this anomalous diffusion is characterised by crossovers between regimes with different anomalous diffusion exponents alpha(i). Here we consider the case when such a crossover occurs from a first regime with alpha(1) to a second regime with alpha(2) such that alpha(2) > alpha(1), i.e., accelerating anomalous diffusion. A widely used framework to describe such crossovers in a one-dimensional setting is the bi-fractional diffusion equation of the so-called modified type, involving two time-fractional derivatives defined in the Riemann-Liouville sense. We here generalise this bi-fractional diffusion equation to higher dimensions and derive its multidimensional propagator (Green's function) for the general case when also a space fractional derivative is present, taking into consideration long-ranged jumps (Levy flights). We derive the asymptotic behaviours for this propagator in both the short- and long-time as well the short- and long-distance regimes. Finally, we also calculate the mean squared displacement, skewness and kurtosis in all dimensions, demonstrating that in the general case the non-Gaussian shape of the probability density function changes.
We consider a ring network of theta neurons with non-local homogeneous coupling. We analyse the corresponding continuum evolution equation, analytically describing all possible steady states and their stability. By considering a number of different parameter sets, we determine the typical bifurcation scenarios of the network, and put on a rigorous footing some previously observed numerical results.
In the last years, electron density profile functions characterized by a linear dependence on the scale height showed good results when approximating the topside ionosphere. The performance above 800 km, however, is not yet well investigated.
This study investigates the capability of the semi-Epstein functions to represent electron density profiles from the peak height up to 20,000 km. Electron density observations recorded by the Van Allen Probes were used to resolve the scale height dependence in the plasmasphere.
It was found that the linear dependence of the scale height in the topside ionosphere cannot be directly used to extrapolate profiles above 800 km.
We find that the dependence of scale heights on altitude is quadratic in the plasmasphere. A statistical model of the scale heights is therefore proposed. After combining the topside ionosphere and plasmasphere by a unified model, we have obtained good estimations not only in the profile shapes, but also in the Total Electron Content magnitude and distributions when compared to actual measurements from 2013, 2014, 2016 and 2017.
Our investigation shows that Van Allen Probes can be merged to radio-occultation data to properly represent the upper ionosphere and plasmasphere by means of a semi-Epstein function.
Active matter broadly covers the dynamics of self-propelled particles.
While the onset of collective behavior in homogenous active systems is relatively well understood, the effect of inhomogeneities such as obstacles and traps lacks overall clarity.
Here, we study how interacting, self-propelled particles become trapped and released from a trap.
We have found that captured particles aggregate into an orbiting condensate with a crystalline structure. As more particles are added, the trapped condensates escape as a whole.
Our results shed light on the effects of confinement and quenched disorder in active matter.
Manipulating spin waves is highly required for the development of innovative data transport and processing technologies. Recently, the possibility of triggering high-frequency standing spin waves in magnetic insulators using femtosecond laser pulses was discovered, raising the question about how one can manipulate their dynamics. Here we explore this question by investigating the ultrafast magnetiza-tion and spin-wave dynamics induced by double-pulse laser excitation. We demonstrate a suppression or enhancement of the amplitudes of the standing spin waves by precisely tuning the time delay between the two pulses. The results can be understood as the constructive or destructive interference of the spin waves induced by the first and second laser pulses. Our findings open exciting perspectives towards generating single-mode standing spin waves that combine high frequency with large amplitude and low magnetic damping.
Plasmon-driven dehalogenation of brominated purines has been recently explored as a model system to understand fundamental aspects of plasmon-assisted chemical reactions. Here, it is shown that divalent Ca2+ ions strongly bridge the adsorption of bromoadenine (Br-Ade) to Ag surfaces.
Such ion-mediated binding increases the molecule's adsorption energy leading to an overlap of the metal energy states and the molecular states, enabling the chemical interface damping (CID) of the plasmon modes of the Ag nanostructures (i.e., direct electron transfer from the metal to Br-Ade).
Consequently, the conversion of Br-Ade to adenine almost doubles following the addition of Ca2+.
These experimental results, supported by theoretical calculations of the local density of states of the Ag/Br-Ade complex, indicate a change of the charge transfer pathway driving the dehalogenation reaction, from Landau damping (in the lack of Ca2+ ions) to CID (after the addition of Ca2+).
The results show that the surface dynamics of chemical species (including water molecules) play an essential role in charge transfer at plasmonic interfaces and cannot be ignored. It is envisioned that these results will help in designing more efficient nanoreactors, harnessing the full potential of plasmon-assisted chemistry.
This paper studies cosmic-ray (CR) transport in magnetohydrodynamic (MHD) turbulence. CR transport is strongly dependent on the properties of the magnetic turbulence.
We perform test particle simulations to study the interactions of CR with both total MHD turbulence and decomposed MHD modes.
The spatial diffusion coefficients and the pitch angle scattering diffusion coefficients are calculated from the test particle trajectories in turbulence.
Our results confirm that the fast modes dominate the CR propagation, whereas Alfven and slow modes are much less efficient and have shown similar pitch-angle scattering rates.
We investigate the cross field transport on large and small scales. On large/global scales, normal diffusion is observed and the diffusion coefficient is suppressed by M-A(zeta) compared to the parallel diffusion coefficients, with zeta closer to 4 in Alfven modes than that in total turbulence, as theoretically expected.
For the CR transport on scales smaller than the turbulence injection scale, both the local and global magnetic reference frames are adopted. Superdiffusion is observed on such small scales in all the cases. Particularly, CR transport in Alfven modes show clear Richardson diffusion in the local reference frame. The diffusion transitions smoothly from the Richardson's one with index 1.5 to normal diffusion as the particle mean free path decreases from lambda(parallel to) >> L to lambda(parallel to) << L, where L is the injection/coherence length of turbulence.
Our results have broad applications to CRs in various astrophysical environments.
Modelling of an open quantum system requires knowledge of parameters that specify how it couples to its environment. However, beyond relaxation rates, realistic parameters for specific environments and materials are rarely known. Here we present a method of inferring the coupling between a generic system and its bosonic (e.g., phononic) environment from the experimentally measurable density of states (DOS). With it we confirm that the DOS of the well-known Debye model for three-dimensional solids is physically equivalent to choosing an Ohmic bath. We further match a real phonon DOS to a series of Lorentzian coupling functions, allowing us to determine coupling parameters for gold, yttrium iron garnet (YIG) and iron as examples. The results illustrate how to obtain material-specific dynamical properties, such as memory kernels. The proposed method opens the door to more accurate modelling of relaxation dynamics, for example for phonon-dominated spin damping in magnetic materials.
The fluctuating hydrogen bridge bonded network of liquid water at ambient conditions entails a varied ensemble of the underlying constituting H2O molecular moieties. This is mirrored in a manifold of the H2O molecular potentials. Subnatural line width resonant inelastic X-ray scattering allowed us to quantify the manifold of molecular potential energy surfaces along the H2O symmetric normal mode and the local asymmetric O-H bond coordinate up to 1 and 1.5 angstrom, respectively. The comparison of the single H2O molecular potentials and spectroscopic signatures with the ambient conditions liquid phase H2O molecular potentials is done on various levels. In the gas phase, first principles, Morse potentials, and stepwise harmonic potential reconstruction have been employed and benchmarked. In the liquid phase the determination of the potential energy manifold along the local asymmetric O-H bond coordinate from resonant inelastic X-ray scattering via the bound state oxygen ls to 4a(1) resonance is treated within these frameworks. The potential energy surface manifold along the symmetric stretch from resonant inelastic X-ray scattering via the oxygen 1 s to 2b(2) resonance is based on stepwise harmonic reconstruction. We find in liquid water at ambient conditions H2O molecular potentials ranging from the weak interaction limit to strongly distorted potentials which are put into perspective to established parameters, i.e., intermolecular O-H, H-H, and O-O correlation lengths from neutron scattering.
The random nature of self-amplified spontaneous emission (SASE) is a well-known challenge for x-ray core level spectroscopy at SASE free-electron lasers (FELs). Especially in time-resolved experiments that require a combination of good temporal and spectral resolution the jitter and drifts in the spectral characteristics, relative arrival time as well as power fluctuations can smear out spectral-temporal features. We present a combination of methods for the analysis of time-resolved photoelectron spectra based on power and time corrections as well as self-referencing of a strong photoelectron line. Based on sulfur 2p photoelectron spectra of 2-thiouracil taken at the SASE FEL FLASH2, we show that it is possible to correct for some of the photon energy drift and jitter even when reliable shot-to-shot photon energy data is not available. The quality of pump-probe difference spectra improves as random jumps in energy between delay points reduce significantly. The data analysis allows to identify coherent oscillations of 1 eV shift on the mean photoelectron line of 4 eV width with an error of less than 0.1 eV.
Recently, a large number of research teams from around the world collaborated in the so-called 'anomalous diffusion challenge'. Its aim: to develop and compare new techniques for inferring stochastic models from given unknown time series, and estimate the anomalous diffusion exponent in data. We use various numerical methods to directly obtain this exponent using the path increments, and develop a questionnaire for model selection based on feature analysis of a set of known stochastic processes given as candidates. Here, we present the theoretical background of the automated algorithm which we put for these tasks in the diffusion challenge, as a counter to other pure data-driven approaches.
Concentrating Solar Power (CSP) offers flexible and decarbonized power generation and is one of the few dispatchable renewable technologies able to generate renewable electricity on demand. Today (2018) CSP contributes only 5TWh to the European power generation, but it has the potential to become one of the key pillars for European decarbonization pathways. In this paper we investigate how factors and pivotal policy decisions leading to different futures and associated CSP deployment in Europe in the years up to 2050. In a second step we characterize the scenarios with their associated system cost and the costs of support policies. We show that the role of CSP in Europe critically depends on political developments and the success or failure of policies outside renewable power. In particular, the uptake of CSP depends on the overall decarbonization ambition, the degree of cross border trade of renewable electricity and is enabled by the presence of strong grid interconnection between Southern and Norther European Member States as well as by future electricity demand growth. The presence of other baseload technologies, prominently nuclear power in France, reduce the role and need for CSP. Assuming favorable technological development, we find a strong role for CSP in Europe in all modeled scenarios: contributing between 100TWh to 300TWh of electricity to a future European power system. This would require increasing the current European CSP fleet by a factor of 20 to 60 in the next 30 years. To achieve this financial support between € 0.4-2 billion per year into CSP would be needed, representing only a small share of overall support needs for power-system transformation. Cooperation of Member States could further help to reduce this cost.
In recent years, gravitational-wave astronomy has motivated increasingly accurate perturbative studies of gravitational dynamics in compact binaries. This in turn has enabled more detailed analyses of the dynamical black holes in these systems. For example, Pound et al. [Phys. Rev. Lett. 124, 021101 (2020)] recently computed the surface area of a Schwarzschild black hole's apparent horizon, perturbed by an orbiting body, to second order in the binary's mass ratio. In this paper, we take that as the starting point for a comprehensive study of a perturbed Schwarzschild black hole's apparent and event horizon at second perturbative order, deriving generic formulas for the first- and second-order corrections to the horizons' radial profiles, surface areas, Hawking masses, and intrinsic curvatures. We find that the two horizons are remarkably similar, and that any teleological behavior of the event horizon is suppressed in several ways. Critically, we establish that at all orders, the perturbed event horizon in a small-mass-ratio binary is effectively localized in time. Even more pointedly, the event horizon is identical to the apparent horizon at linear order regardless of the source of perturbation, implying that the seemingly teleological "tidal lead," previously observed in linearly perturbed event horizons, is not genuinely teleological in origin. The two horizons do generically differ at second order, but their Hawking masses remain identical, implying that the event horizon obeys the same energy-flux balance law as the apparent horizon. At least in the case of a binary system, the difference between their surface areas remains extremely small even in the late stages of inspiral. In the course of our analysis, we also numerically illustrate puzzling behavior in the black hole's motion around the binary's center of mass.
In this paper, we present a study comparing the depth to diameter (d/D) ratio of small simple craters (200-1000 m) of an area between -88.5 degrees to -90 degrees latitude at the lunar south pole containing Permanent Shadowed Regions (PSRs) versus craters without PSRs. As PSRs can reach temperatures of 110 K and are capable of harboring volatiles, especially water ice, we analyzed the relationship of depth versus diameter ratios and its possible implications for harboring water ice. Variations in the d/D ratios can also be caused by other processes such as degradation, isostatic adjustment, or differences in surface properties. The conducted d/D ratio analysis suggests that a differentiation between craters containing PSRs versus craters without PSRs occurs. Thus, a possible direct relation between d/D ratio, PSRs, and water ice harboring might exist. Our results suggest that differences in the target's surface properties may explain the obtained results. The resulting d/D ratios of craters with PSRs can help to select target areas for future In-Situ Resource Utilization (ISRU) missions.
Only a fast and global transformation towards decarbonization and sustainability can keep the Earth in a civilization-friendly state. As hotspots for (green) innovation and experimentation, cities could play an important role in this transition. They are also known to profit from each other's ideas, with policy and technology innovations spreading to other cities. In this way, cities can be conceptualized as nodes in a globe-spanning learning network. The dynamics of this process are important for society's response to climate change and other challenges, but remain poorly understood on a macroscopic level. In this contribution, we develop an approach to identify whether network-based complex contagion effects are a feature of sustainability policy adoption by cities, based on dose-response contagion and surrogate data models. We apply this methodology to an exemplary data set, comprising empirical data on the spreading of a public transport innovation (Bus Rapid Transit Systems) and a global inter-city connection network based on scheduled flight routes. Although our approach is not able to identify detailed mechanisms, our results point towards a contagious spreading process, and cannot be explained by either the network structure or the increase in global adoption rate alone. Further research on the role of a city's abstract "global neighborhood" regarding its policy and innovation decisions is thus both needed and promising, and may connect with research on social tipping processes. The methodology is generic, and can be used to compare the predictive power for innovation spreading of different kinds of inter-city network connections, e.g. via transport links, trade, or co-membership in political networks.
Lennard-Jones mixtures represent one of the popular systems for the study of glass-forming liquids.
Spatio/temporal heterogeneity and rare (activated) events are at the heart of the slow dynamics typical of these systems. Such slow dynamics is characterised by the development of a plateau in the mean-squared displacement (MSD) at intermediate times, accompanied by a non-Gaussianity in the displacement distribution identified by exponential tails.
As pointed out by some recent works, the non-Gaussianity persists at times beyond the MSD plateau, leading to a Brownian yet non-Gaussian regime and thus highlighting once again the relevance of rare events in such systems.
Single-particle motion of glass-forming liquids is usually interpreted as an alternation of rattling within the local cage and cage-escape motion and therefore can be described as a sequence of waiting times and jumps. In this work, by using a simple yet robust algorithm, we extract jumps and waiting times from single-particle trajectories obtained via molecular dynamics simulations.
We investigate the presence of correlations between waiting times and find negative correlations, which becomes more and more pronounced when lowering the temperature.
The increase in the performance of organic solar cells observed over the past few years has reinvigorated the search for a deeper understanding of the loss and extraction processes in this class of device. A detailed knowledge of the density of free charge carriers under different operating conditions and illumination intensities is a prerequisite to quantify the recombination and extraction dynamics. Differential charging techniques are a promising approach to experimentally obtain the charge carrier density under the aforementioned conditions. In particular, the combination of transient photovoltage and photocurrent as well as impedance and capacitance spectroscopy have been successfully used in past studies to determine the charge carrier density of organic solar cells. In this Tutorial, these experimental techniques will be discussed in detail, highlighting fundamental principles, practical considerations, necessary corrections, advantages, drawbacks, and ultimately their limitations. Relevant references introducing more advanced concepts will be provided as well. Therefore, the present Tutorial might act as an introduction and guideline aimed at new prospective users of these techniques as well as a point of reference for more experienced researchers. Published under an exclusive license by AIP Publishing.
Diffraction enhanced imaging (DEI) is an advanced digital radiographic imaging technique employing the refraction of X-rays to contrast internal interfaces. This study aims to qualitatively and quantitatively evaluate images acquired using this technique and to assess how different fitting functions to the typical rocking curves (RCs) influence the quality of the images. RCs are obtained for every image pixel. This allows the separate determination of the absorption and the refraction properties of the material in a position-sensitive manner. Comparison of various types of fitting functions reveals that the Pseudo-Voigt (PsdV) function is best suited to fit typical RCs. A robust algorithm was developed in the Python programming language, which reliably extracts the physically meaningful information from each pixel of the image. We demonstrate the potential of the algorithm with two specimens: a silicone gel specimen that has well-defined interfaces, and an additively manufactured polycarbonate specimen.
A magnetic field modifies optical properties and provides valley splitting in a molybdenum disulfide (MoS2) monolayer.
Here we demonstrate a scalable approach to the epitaxial synthesis of MoS2 monolayer on a magnetic graphene/Co system.
Using spin- and angle-resolved photoemission spectroscopy we observe a magnetic proximity effect that causes a 20 meV spin-splitting at the (Gamma) over bar point and canting of spins at the (K) over bar point in the valence band toward the in-plane direction of cobalt magnetization.
Our density functional theory calculations reveal that the in-plane spin component at (K) over bar is localized on Co atoms in the valence band, while in the conduction band it is localized on the MoS2 layer.
The calculations also predict a 16 meV spin-splitting at the (Gamma) over bar point and 8 meV (K) over bar-(K) over bar' valley asymmetry for an out-of-plane magnetization. These findings suggest control over optical transitions in MoS2 via Co magnetization. Our estimations show that the magnetic proximity effect is equivalent to the action of the magnetic field as large as 100 T.
Isoflux tension propagation (IFTP) theory and Langevin dynamics (LD) simulations are employed to study the dynamics of channel-driven polymer translocation in which a polymer translocates into a narrow channel and the monomers in the channel experience a driving force fc. In the high driving force limit, regardless of the channel width, IFTP theory predicts τ ∝ f βc for the translocation time, where β = −1 is the force scaling exponent. Moreover, LD data show that for a very narrow channel fitting only a single file of monomers, the entropic force due to the subchain inside the channel does not play a significant role in the translocation dynamics and the force exponent β = −1 regardless of the force magnitude. As the channel width increases the number of possible spatial configurations of the subchain inside the channel becomes significant and the resulting entropic force causes the force exponent to drop below unity.
Organic solar cells (OSCs) have progressed rapidly in recent years through the development of novel organic photoactive materials, especially non-fullerene acceptors (NFAs). Consequently, OSCs based on state-of-the-art NFAs have reached significant milestones, such as similar to 19% power conversion efficiencies (PCEs) and small energy losses (less than 0.5 eV). Despite these significant advances, understanding of the interplay between molecular structure and optoelectronic properties lags significantly behind. For example, despite the theoretical framework for describing the energetic disorder being well developed for the case of inorganic semiconductors, the question of the applicability of classical semiconductor theories in analyzing organic semiconductors is still under debate. A general observation in the inorganic field is that inorganic photovoltaic materials possessing a polycrystalline microstructure exhibit suppressed disorder properties and better charge carrier transport compared to their amorphous analogs. Accordingly, this principle extends to the organic semiconductor field as many organic photovoltaic materials are synthesized to pursue polycrystalline-like features. Yet, there appears to be sporadic examples that exhibit an opposite trend. However, full studies decoupling energetic disorder from aggregation effects have largely been left out. Hence, the potential role of the energetic disorder in OSCs has received little attention. Interestingly, recently reported state-of-the-art NFA-based devices could achieve a small energetic disorder and high PCE at the same time; and interest in this investigation related to the disorder properties in OSCs was revived. In this contribution, progress in terms of the correlation between molecular design and energetic disorder is reviewed together with their effects on the optoelectronic mechanism and photovoltaic performance. Finally, the specific challenges and possible solutions in reducing the energetic disorder of OSCs from the viewpoint of materials and devices are proposed.
We study the ultrafast electronic transport of energy in a photoexcited nanoscale Au/Fe hetero-structure by modeling the spatiotemporal profile of energy densities that drives transient strain, which we quantify by femtosecond x-ray diffraction. This flow of energy is relevant for intrinsic demagnetization and ultrafast spin transport. We measured lattice strain for different Fe layer thicknesses ranging from few atomic layers to several nanometers and modeled the spatiotemporal flow of energy densities. The combination of a high electron-phonon coupling coefficient and a large Sommerfeld constant in Fe is found to yield electronic transfer of nearly all energy from Au to Fe within the first hundreds of femtoseconds.
In this work, the fabrication and characterization of a simple, inexpensive, and effective microfluidic paper analytic device (mu PAD) for monitoring DNA samples is reported. The glass microfiber-based chip has been fabricated by a new wax-based transfer-printing technique and an electrode printing process. It is capable of moving DNA effectively in a time-dependent fashion. The nucleic acid sample is not damaged by this process and is accumulated in front of the anode, but not directly on the electrode. Thus, further DNA processing is feasible. The system allows the DNA to be purified by separating it from other components in sample mixtures such as proteins. Furthermore, it is demonstrated that DNA can be moved through several layers of the glass fiber material. This proof of concept will provide the basis for the development of rapid test systems, e.g., for the detection of pathogens in water samples.
Im Lehramtsstudium sollen Studierende grundlegende Fähigkeiten zur theoriegeleiteten Unterrichtsplanung erwerben.
In Übereinstimmung mit Modellen zur professionellen Handlungskompetenz von Lehrkräften wird hierbei meist angenommen, dass das im Studienverlauf erworbene Professionswissen eine wesentliche Grundlage für den Aufbau von Fähigkeiten zur Unterrichtsplanung bildet.
Lerngelegenheiten zur Anwendung dieses Professionswissens bieten vor allem schulpraktische Phasen im fortgeschrittenen Studienverlauf. Es wird aber ebenso angenommen, dass gerade Erfahrungen mit der Unterrichtsplanung den Aufbau von Professionswissen unterstützen.
Der Zusammenhang zwischen dem Ausmaß des Professionswissens und der Entwicklung von Planungsfähigkeit ist bisher unzureichend empirisch geklärt. Eine besondere methodische Herausforderung besteht darin, Planungsfähigkeiten sowohl möglichst authentisch als auch auf standardisierte Weise zu erfassen. Zur Untersuchung des genannten Zusammenhangs wurde eine längsschnittliche Studie im Prä-Post-Design bei angehenden Physiklehrkräften (N = 68 im Längsschnitt) an vier Universitäten durchgeführt.
Die Unterrichtsplanungsfähigkeit wurde mit Hilfe eines standardisierten Performanztests vor und nach dem Absolvieren eines Praxissemesters erfasst, indem als Standardsituation der Entwurf einer Unterrichtsstunde zum 3. Newton’schen Axiom unter definierten Zeitvorgaben im Praxissemester simuliert wurde. Zusätzlich wurden das fachliche, fachdidaktische und pädagogische Wissen der Studierenden mit Hilfe standardisierter Instrumente zu beiden Zeitpunkten erhoben, sowie die einschlägigen Lerngelegenheiten im Praxissemester über einen Fragebogen erfasst.
Sowohl für Unterrichtsplanungsfähigkeit als auch für alle Wissensvariablen können Zuwächse im Praxissemester beobachtet werden. Cross-Lagged-Panel-Analysen zeigen, dass insbesondere die Ausprägung des fachdidaktischen und pädagogischen Wissens der Studierenden am Beginn des Praxissemesters die Entwicklung von Unterrichtsplanungsfähigkeit begünstigt.
Populations of globally coupled phase oscillators are described in the thermodynamic limit by kinetic equations for the distribution densities or, equivalently, by infinite hierarchies of equations for the order parameters. Ott and Antonsen [Chaos 18, 037113 (2008)] have found an invariant finite-dimensional subspace on which the dynamics is described by one complex variable per population. For oscillators with Cauchy distributed frequencies or for those driven by Cauchy white noise, this subspace is weakly stable and, thus, describes the asymptotic dynamics. Here, we report on an exact finite-dimensional reduction of the dynamics outside of the Ott-Antonsen subspace. We show that the evolution from generic initial states can be reduced to that of three complex variables, plus a constant function. For identical noise-free oscillators, this reduction corresponds to the Watanabe-Strogatz system of equations [Watanabe and Strogatz, Phys. Rev. Lett. 70, 2391 (1993)]. We discuss how the reduced system can be used to explore the transient dynamics of perturbed ensembles. Published under an exclusive license by AIP Publishing.
The electronic and magnetic excitations of bulk NiO have been determined using the 3A2g to 3T2g crystal-field transition at the Ni M2,3 edges with resonant inelastic x-ray scattering at 66.3- and 67.9-eV photon energies and 33-meV spectral resolution. Unambiguous assignment of the high-energy side of this state to a spin-flip satellite is achieved. We extract an effective exchange field of 89±4 meV in the 3T2g excited final state from empirical two-peak spin-flip model. The experimental data is found consistent with crystal-field model calculations using exchange fields of 60–100 meV. Full agreement with crystal-field multiplet calculations is achieved for the incident photon energy dependence of line shapes. The lower exchange parameter in the excited state as compared to the ground-state value of 120 meV is discussed in terms of the modification of the orbital occupancy (electronic effects) and of the structural dynamics: (A) With pure electronic effects, the lower exchange energy is attributed to the reduction in effective hopping integral. (B) With no electronic effects, we use the S = 1 Heisenberg model of antiferromagnetism to derive a second-nearest-neighbor exchange constant J2 = 14.8±0.6 meV. Based on the linear correlation between J2 and the lattice parameter from pressure-dependent experiments, an upper limit of 2% local Ni-O bond elongation during the femtosecond scattering duration is derived.