Spatio-temporal Reconstruction Research Articles

Comparative studies of compact kHz and MHz driven low pressure plasmas by emission and laser spectroscopy

The temporal evolution of a low pressure argon plasma driven by a combination of radio frequency and kilohertz frequency power sources was characterized by phase resolved optical emission and laser absorption spectroscopy. The compact, low pressure plasma was formed in a hybrid surface/jet geometry and powered by a high voltage power supply operating at 31 kHz and by a lower voltage RF supply operating at 13.56 MHz. An accurate evaluation of the 1s state density dynamics was performed by means of laser absorption measurements of the 1s5 and 1s4 sublevels. The emission spectra were recorded with a submicrosecond temporal resolution and evaluated using an extended Corona model. In comparison with the modeling results, the phase dependent ratio of different Ar(2p) → Ar(1s) emission lines was used to determine temporal profiles of electron temperature and relative electron density. The results were compared with the results from time averaged emission measurements by performing an identical analysis. Strong spatial and temporal variations of plasma parameters were observed when the plasma was driven solely by the 31 kHz source, resulting in nonequilibrium conditions for long living states. Inconsistent observations in the reconstructed temporal development of plasma energy and density were further investigated by illustrating full spatiotemporal reconstruction of plasma parameters. These results permit clear identification of strong spatial gradients through the tube.

Spatiotemporal data fusion and manifold reconstruction in Hall thrusters**Distribution Statement A: Approved for Public Release. Distribution is Unlimited. PA# 18635.

A critical breakthrough in the understanding of Hall effect thrusters (HETs) has been the emergence of mapping techniques to fuse multiple time-varying plasma measurements from spatially distributed probes into a unified reconstruction describing the full spatiotemporal dynamics of the HET plasma. The most basic requirement for generating such a spatiotemporal reconstruction is a robust and accurate method to build a map between a single input and a single output signal. This work describes a new nonlinear phase space based mapping technique, the shadow manifold interpolation (SMI) technique, and assesses its performance versus traditional linear FFT-based mapping. Results demonstrate the superiority of the SMI reconstruction for short, noisy and aperiodic signals. Analysis in conjunction with the convergent cross mapping methodology (Sugihara et al 2012 Science 338 496–500) provides theoretical justification for the physical relevance of SMI application to a given signal reconstruction.

Spatiotemporal patterns of pre-Columbian people in Amazonia

AbstractA current goal among many scientific disciplines is to incorporate data on past human land use and climate change into current global climate and vegetation models. Here, we used existing archaeological and paleoecological data to provide a spatiotemporal reconstruction of human history in Greater Amazonia over the Holocene. We used an ensemble distribution model based on a database of georeferenced14C-dated material and environmental factors to predict the changes in spatial distributions of past human occupation sites. We ran these models for the precultivation (13,000–6000 yr ago), early cultivation (6000–2500 yr ago), and late cultivation (2500–500 yr ago) periods. The ensemble models suggest that people mostly inhabited the peripheral areas of Greater Amazonia and the eastern sections of the main Amazon River and its larger tributaries during the precultivation period. Human populations began growing exponentially through the early cultivation period, and people spread and expanded into the interior forests and along river channels in western Amazonia. Populations continued growing through the late cultivation period in these same regions. Our results suggest that many forests, particularly in the peripheral regions and riverine locations, may still be in recovery from disturbances that have occurred repeatedly through the Holocene.

Reconstruction and actual trends of landslide activities in Bruust–Haltiwald, Horw, canton of Lucerne, Switzerland

Abstract. A spatiotemporal reconstruction of slope movements on the edge of Lake Lucerne near the municipality of Horw, canton of Lucerne, is presented. The reconstruction was realized by analyzing growth reactions of beech (Fagus sylvatica L.) and fir (Abies alba Mill.) trees growing on this slope. Before dendrochronological sampling, a detailed geomorphological mapping of the landslide was conducted with the aim to determine the spatial extent of the sliding area. For tree-ring analyses, 124 increment cores from 62 trees were analyzed following standard techniques of dendrogeomorphology. In addition, long micro-sections were prepared from the entire cores to extend the common eccentricity analyses by microscopic determination of the onset of reaction wood in fir and beech. Results clearly show that the area is moving at least since 1948. A significant concentration of events was observed between the years 1990 and 2000 as well as after 2006. The definition of a threshold to define events using an eccentricity index alone is problematic and needs to be adapted to specific site conditions. For this reason, we recommend always combining the application of an eccentricity index with a detailed visual (anatomical) inspection to check for the occurrence of reaction wood.

Feasibility of multiple-view myocardial perfusion MRI using radial simultaneous multi-slice acquisitions.

PurposeDynamic contrast enhanced MRI of the heart typically acquires 2–4 short-axis (SA) slices to detect and characterize coronary artery disease. This acquisition scheme is limited by incomplete coverage of the left ventricle. We studied the feasibility of using radial simultaneous multi-slice (SMS) technique to achieve SA, 2-chamber and/or 4-chamber long-axis (2CH LA and/or 4CH LA) coverage with and without electrocardiography (ECG) gating using a motion-robust reconstruction framework.Methods12 subjects were scanned at rest and/or stress, free breathing, with or without ECG gating. Multiple sets of radial SMS k-space were acquired within each cardiac cycle, and each SMS set sampled 3 parallel slices that were either SA, 2CH LA, or 4CH LA slices. The radial data was interpolated onto Cartesian space using an SMS GRAPPA operator gridding method. Self-gating and respiratory states binning of the data were done. The binning information as well as a pixel tracking spatiotemporal constrained reconstruction method were applied to obtain motion-robust image reconstructions. Reconstructions with and without the pixel tracking method were compared for signal-to-noise ratio and contrast-to-noise ratio.ResultsFull coverage of the heart (at least 3 SA and 3 LA slices) during the first pass of contrast at every heartbeat was achieved by using the radial SMS acquisition. The proposed pixel tracking reconstruction improves the average SNR and CNR by 21% and 30% respectively, and reduces temporal blurring for both gated and ungated acquisitions.ConclusionAcquiring simultaneous multi-slice SA, 2CH LA and/or 4CH LA myocardial perfusion images in every heartbeat is feasible in both gated and ungated acquisitions. This can add confidence when detecting and characterizing coronary artery disease by revealing ischemia in different views, and by providing apical coverage that is improved relative to SA slices alone. The proposed pixel tracking framework improves the reconstruction while adding little computational cost.

Spatiotemporal imaging of plasmonic fields near nanoparticles below the diffraction limit

Optically induced collective conduction-electron oscillations can generate intense plasmonic fields near metallic nanoparticles. We suggest a method for reconstructing such nanoplasmonic fields with nanometer spatial and sub-femtosecond temporal resolution from streaked photoemission spectra. Applying this imaging scheme to Au nanospheres, we demonstrate the accurate spatiotemporal reconstruction of the plasmonic near-field distribution in comparison with the directly calculated plasmonic field.

Neural Network Based Kalman Filters for the Spatio-Temporal Interpolation of Satellite-Derived Sea Surface Temperature

The forecasting and reconstruction of oceanic dynamics is a crucial challenge. While model driven strategies are still the state-of-the-art approaches in the reconstruction of spatio-temporal dynamics. The ever increasing availability of data collections in oceanography raised the relevance of data-driven approaches as computationally efficient representations of spatio-temporal fields reconstruction. This tools proved to outperform classical state-of-the-art interpolation techniques such as optimal interpolation and DINEOF in the retrievement of fine scale structures while still been computationally efficient comparing to model based data assimilation schemes. However, coupling this data-driven priors to classical filtering schemes limits their potential representativity. From this point of view, the recent advances in machine learning and especially neural networks and deep learning can provide a new infrastructure for dynamical modeling and interpolation within a data-driven framework. In this work we adress this challenge and develop a novel Neural-Network-based (NN-based) Kalman filter for spatio-temporal interpolation of sea surface dynamics. Based on a data-driven probabilistic representation of spatio-temporal fields, our approach can be regarded as an alternative to classical filtering schemes such as the ensemble Kalman filters (EnKF) in data assimilation. Overall, the key features of the proposed approach are two-fold: (i) we propose a novel architecture for the stochastic representation of two dimensional (2D) geophysical dynamics based on a neural networks, (ii) we derive the associated parametric Kalman-like filtering scheme for a computationally-efficient spatio-temporal interpolation of Sea Surface Temperature (SST) fields. We illustrate the relevance of our contribution for an OSSE (Observing System Simulation Experiment) in a case-study region off South Africa. Our numerical experiments report significant improvements in terms of reconstruction performance compared with operational and state-of-the-art schemes (e.g., optimal interpolation, Empirical Orthogonal Function (EOF) based interpolation and analog data assimilation).

3D morphology and timing of the giant fossil pockmark of Beauvoisin, SE Basin of France

The resolution of data acquired over modern seafloors does not allow imaging of the inner features of a fluid seep structure, particularly in the shallow subsurface. In the SE Basin of France (Drôme), fossil cold seep structures comprising fossil-rich carbonate lenses were identified about 30 years ago within the Oxfordian (Late Jurassic) Terres Noires Formation. These structures were first interpreted as pseudo-bioherms related to hydrothermal activity, but comparison with active seep sites on modern margins, together with isotopic analyses, led to a reinterpretation involving cold fluids instead. To date, all seep sites have generally been studied individually without considering any link to neighbouring or more distant sites. Based on 23 high-resolution stratigraphic logs within the structure coupled to mosaicked aerial photographs from a drone survey, 19 fluid seep events were correlated in the area, including two new sites exposed as a result of weathering. We have shown that each identified sub-site is composed of subvertically stacked fossil-rich carbonate lenses interbedded with marls, which developed in smooth, 4–6 m deep depressions beneath the local seabed. The nodules present within the depressions are of primary importance as they mark the area of active seeping. This general organization is very similar to the modern Regab giant pockmark in the Lower Congo Basin where only a few sub-sites are active at the same time. A spatio-temporal 3D reconstruction of the position of these sub-sites shows that the carbonate lenses are organized into clusters comprising up to seven sub-sites grouped together in the same stratigraphic interval and the same geographical zone. A sandbox experiment where gas is injected at constant flow rate at the base of a box filled with a matrix of water-saturated grains displays a pattern consisting of disturbed sediments inside a parabolic-shaped area. This parabolic shape was also identified on a seismic profile across the Regab giant pockmark, suggesting that the processes are similar for the Beauvoisin and Regab seep areas. The laboratory experiments also show that the seeping conduit is stable during a given period of time and suddenly shifts laterally. This is mainly as a result of the collapse of the conduit, the lateral migration and the reopening at a new position. The general log obtained in the Beauvoisin seep area suggests a similar pattern with periods of seeping alternating with periods of quiescence, each of which is c . 200 kyr. Even if a pockmark seems to have been inactive for a long period of time, this could be due to the lateral shift of the feeder conduit, meaning that the sub-seafloor is still charged with gas. This is of primary importance for risk assessment, hydrocarbon exploration and general understanding of geobiology at seafloor seeps.

Localization of Active Brain Sources From EEG Signals Using Empirical Mode Decomposition: A Comparative Study.

The localization of active brain sources from Electroencephalogram (EEG) is a useful method in clinical applications, such as the study of localized epilepsy, evoked-related-potentials, and attention deficit/hyperactivity disorder. The distributed-source model is a common method to estimate neural activity in the brain. The location and amplitude of each active source are estimated by solving the inverse problem by regularization or using Bayesian methods with spatio-temporal constraints. Frequency and spatio-temporal constraints improve the quality of the reconstructed neural activity. However, separation into frequency bands is beneficial when the relevant information is in specific sub-bands. We improved frequency-band identification and preserved good temporal resolution using EEG pre-processing techniques with good frequency band separation and temporal resolution properties. The identified frequency bands were included as constraints in the solution of the inverse problem by decomposing the EEG signals into frequency bands through various methods that offer good frequency and temporal resolution, such as empirical mode decomposition (EMD) and wavelet transform (WT). We present a comparative analysis of the accuracy of brain-source reconstruction using these techniques. The accuracy of the spatial reconstruction was assessed using the Wasserstein metric for real and simulated signals. We approached the mode-mixing problem, inherent to EMD, by exploring three variants of EMD: masking EMD, Ensemble-EMD (EEMD), and multivariate EMD (MEMD). The results of the spatio-temporal brain source reconstruction using these techniques show that masking EMD and MEMD can largely mitigate the mode-mixing problem and achieve a good spatio-temporal reconstruction of the active sources. Masking EMD and EEMD achieved better reconstruction than standard EMD, Multiple Sparse Priors, or wavelet packet decomposition when EMD was used as a pre-processing tool for the spatial reconstruction (averaged over time) of the brain sources. The spatial resolution obtained using all three EMD variants was substantially better than the use of EMD alone, as the mode-mixing problem was mitigated, particularly with masking EMD and EEMD. These findings encourage further exploration into the use of EMD-based pre-processing, the mode-mixing problem, and its impact on the accuracy of brain source activity reconstruction.

Missing observation approximation for spatio-temporal profile reconstruction in participatory sensor networks

Purpose Participatory wireless sensor networks (PWSN) is an emerging paradigm that leverages existing sensing and communication infrastructures for the sensing task. Various environmental phenomenon – P monitoring applications dealing with noise pollution, road traffic, requiring spatio-temporal data samples of P (to capture its variations and its profile construction) in the region of interest – can be enabled using PWSN. Because of irregular distribution and uncontrollable mobility of people (with mobile phones), and their willingness to participate, complete spatio-temporal (CST) coverage of P may not be ensured. Therefore, unobserved data values must be estimated for CST profile construction of P and presented in this paper. Design/methodology/approach In this paper, the estimation of these missing data samples both in spatial and temporal dimension is being discussed, and the paper shows that non-parametric technique – Kernel Regression – provides better estimation compared to parametric regression techniques in PWSN context for spatial estimation. Furthermore, the preliminary results for estimation in temporal dimension have been provided. The deterministic and stochastic approaches toward estimation in the context of PWSN have also been discussed. Findings For the task of spatial profile reconstruction, it is shown that non-parametric estimation technique (kernel regression) gives a better estimation of the unobserved data points. In case of temporal estimation, few preliminary techniques have been studied and have shown that further investigations are required to find out best estimation technique(s) which may approximate the missing observations (temporally) with considerably less error. Originality/value This study addresses the environmental informatics issues related to deterministic and stochastic approaches using PWSN.

Lane Detection and Spatiotemporal Reconstruction Using the Macroblock Predictions Method

Detection and tracking of road lane markings offers several applications in intelligent transport systems (ITS). Although it is perceived as the simple task of isolating lanes on various types of roads, the accuracy of detection remains an issue. Several studies in recent literature have proposed solutions to this problem; however, none of these have used the method of macroblock (MB) prediction. This paper focuses on the type of MB applied for lane detection, tracking, and predictions, as well as the trade-off between the accuracy and complexity of implementing the system. This study makes the following contributions: (1) best MB for spatiotemporal lane detection and reconstruction; (2) best function approximation for lane predictions; and (3) best MB in terms of performance under different conditions.

Spatio-temporal super-resolution for multi-videos based on belief propagation

Aiming at improving spatio-temporal resolution of video for real-world applications, this paper focuses on the spatio-temporal super-resolution reconstruction algorithm for multiple asynchronous video sequences. The current multi-video super-resolution algorithms still have some weaknesses in application such as oversimplification of motion, unknown blurring and noise level. For further improvement, a Maximum Posterior Likelihood-Markov Random Field (MAP-MRF) based super-resolution reconstruction method is proposed and proved robust in achieving the real-world super-resolution imaging. The proposed method adopts weighted 3D neighborhood system (WNS) MAP-MRF model to accurately describe the spatial and temporal correlations between multiple video sequences. In order to improve the estimation accuracy of the motions for complex scenes, the improved Scale-Invariant Feature Transform (SIFT) Flow algorithm based on sparsity in wavelet domain is proposed, which can afford the large displacement, rotational movement and other complexities in asynchronous multi-video sequences. The Belief Propagation (BP) algorithm is applied to estimate the parameters of MAP-MRF model, such as motion vector and the super-resolution images in an iterative coarse-to-fine scheme. With the proposed algorithms mentioned above, MAP-MRF based super-resolution reconstruction method has better capabilities of edge sharpness and detailed texture preserving, and robustness of noise suppressing. The experimental result has confirmed the effectiveness of the proposed method under the practical conditions.

A spatiotemporal reconstruction of sea-surface temperatures in the North Atlantic during Dansgaard–Oeschger events 5–8

Abstract. Here, we establish a spatiotemporal evolution of the sea-surface temperatures in the North Atlantic over Dansgaard–Oeschger (DO) events 5–8 (approximately 30–40 kyr) using the proxy surrogate reconstruction method. Proxy data suggest a large variability in North Atlantic sea-surface temperatures during the DO events of the last glacial period. However, proxy data availability is limited and cannot provide a full spatial picture of the oceanic changes. Therefore, we combine fully coupled, general circulation model simulations with planktic foraminifera based sea-surface temperature reconstructions to obtain a broader spatial picture of the ocean state during DO events 5–8. The resulting spatial sea-surface temperature patterns agree over a number of different general circulation models and simulations. We find that sea-surface temperature variability over the DO events is characterized by colder conditions in the subpolar North Atlantic during stadials than during interstadials, and the variability is linked to changes in the Atlantic Meridional Overturning circulation and in the sea-ice cover. Forced simulations are needed to capture the strength of the temperature variability and to reconstruct the variability in other climatic records not directly linked to the sea-surface temperature reconstructions. This is the first time the proxy surrogate reconstruction method has been applied to oceanic variability during MIS3. Our results remain robust, even when age uncertainties of proxy data, the number of available temperature reconstructions, and different climate models are considered. However, we also highlight shortcomings of the methodology that should be addressed in future implementations.

Sedimentological and geomorphological characteristics of Quaternary deposits in the Planica-Tamar Valley in the Julian Alps (NW Slovenia)

ABSTRACTWe present a geomorphological map on a scale of 1:15,000, with detailed sedimentological descriptions, and a general relative spatio-temporal depositional reconstruction of Quaternary sediments in the Planica-Tamar Valley (NW Slovenia). After the Last Glacial Maximum, the retreating Quaternary glacier deposited large amounts of glacial sediments. These were followed by Holocene sediments, which differ in their sedimentological characteristics, transport mechanisms, and morphology. These sediments are deposited as sedimentary bodies with complex depositional geometries. They form areas of active, partly active, and inactive sedimentation in response to local/regional climate and bedrock geology. Previous research of the valley was mainly focused on bedrock mapping, while almost completely neglecting Quaternary deposits. This work is the first broader analysis of Quaternary sedimentary deposits in the research area, which offers an insight into the complex geomorphological and sedimentological processes, which shape the current mountainous landscape.

Single cell expression analysis of primate-specific retroviruses-derived HPAT lincRNAs in viable human blastocysts identifies embryonic cells co-expressing genetic markers of multiple lineages

Chromosome instability and aneuploidies occur very frequently in human embryos, impairing proper embryogenesis and leading to cell cycle arrest, loss of cell viability, and developmental failures in 50–80% of cleavage-stage embryos. This high frequency of cellular extinction events represents a significant experimental obstacle challenging analyses of individual cells isolated from human preimplantation embryos. We carried out single cell expression profiling of 241 individual cells recovered from 32 human embryos during the early and late stages of viable human blastocyst (VHB) differentiation. Classification of embryonic cells was performed solely based on expression patterns of human pluripotency-associated transcripts (HPAT), which represent a family of primate-specific transposable element-derived lincRNAs highly expressed in human embryonic stem cells and regulating nuclear reprogramming and pluripotency induction. We then validated our findings by analyzing transcriptomes of 1,708 individual cells recovered from more than 100 human embryos and 259 mouse cells from more than 40 mouse embryos at different stages of preimplantation embryogenesis. HPAT's expression-guided spatiotemporal reconstruction of human embryonic development inferred from single-cell expression analysis of VHB differentiation enabled identification of telomerase-positive embryonic cells co-expressing key pluripotency regulatory genes and genetic markers of three major lineages. Follow-up validation analyses confirmed the emergence in human embryos prior to lineage segregation of telomerase-positive cells co-expressing genetic markers of multiple lineages. Observations reported in this contribution support the hypothesis of a developmental pathway of creation embryonic lineages and extraembryonic tissues from telomerase-positive pre-lineage cells manifesting multi-lineage precursor phenotype.

Predicting Monsoon Intraseasonal Precipitation using a Low-Order Nonlinear Stochastic Model

Abstract The authors assess the predictability of large-scale monsoon intraseasonal oscillations (MISOs) as measured by precipitation. An advanced nonlinear data analysis technique, nonlinear Laplacian spectral analysis (NLSA), is applied to the daily precipitation data, resulting in two spatial modes associated with the MISO. The large-scale MISO patterns are predicted in two steps. First, a physics-constrained low-order nonlinear stochastic model is developed to predict the highly intermittent time series of these two MISO modes. The model involves two observed MISO variables and two hidden variables that characterize the strong intermittency and random oscillations in the MISO time series. It is shown that the precipitation MISO indices can be skillfully predicted from 20 to 50 days in advance. Second, an effective and practical spatiotemporal reconstruction algorithm is designed, which overcomes the fundamental difficulty in most data decomposition techniques with lagged embedding that requires extra information in the future beyond the predicted range of the time series. The predicted spatiotemporal patterns often have comparable skill to the MISO indices. One of the main advantages of the proposed model is that a short (3 year) training period is sufficient to describe the essential characteristics of the MISO and retain skillful predictions. In addition, both model statistics and prediction skill indicate that outgoing longwave radiation is an accurate proxy for precipitation in describing the MISO. Notably, the length of the lagged embedding window used in NLSA is crucial in capturing the main features and assessing the predictability of MISOs.

Soliton Booting Dynamics in an Ultrafast Anomalous Dispersion Fiber Laser

We reported on the soliton booting dynamics of an ultrafast fiber laser operating in an anomalous dispersion regime. Based on the advanced experimental methodologies of spatio-temporal reconstruction and dispersive Fourier transform (DFT), the soliton booting dynamics are analyzed in the time and spectral domains. The spectral interference pattern with strong intensity oscillation behavior was observed near the mode-locking transition. It was found that the spectral pattern distributions are induced by the transient structured soliton formation during the pulse shaping from the noise background. The experimental results were further verified by the theoretical simulations. The obtained results would provide a general guideline for understanding the soliton booting dynamics in the ultrafast fiber lasers, and will prove to be fruitful to the various communities interested in solitons and fiber lasers.

Three-dimensional organization and dynamics of vortices in multichannel swirling jets

The unsteady three-dimensional flow organization of jets issued from a duct with swirl vanes at Reynolds number equal to 1000 and swirl number $S$ ranging between 0 and 0.8 is investigated. Time-resolved tomographic particle image velocimetry returns the instantaneous flow structure and its evolution by visualization of velocity and vortical features. The most relevant coherent motions are identified and characterized with the aid of dynamic mode decomposition. The time-averaged flow topology indicates that the vanes used to impart the swirling motion have a significant impact on the azimuthal modulation of momentum, with the jet exhibiting four sectors separated by a thin cross-like wake resulting from the boundary layer developed along the vane walls. The flow field is thus characterized by inner and outer shear regions. An increase in swirl, up to moderate levels ($S=0.4$), causes larger jet spreading angles. Further increase of the swirl number is accompanied by the appearance of a central recirculation zone due to vortex breakdown at $S=0.6$ which increases in size and is triggered upstream for increasing $S$. Although no shear layer instability development is observed at $S=0$, already at $S=0.2$ the swirling motion promotes the growth of helical vortices appearing as Kelvin–Helmholtz waves that deform the outer axial shear layer. The downstream evolution features successive pairing, which is observed for all the considered swirl numbers. The initial development of the instability is independent for each vane, whereas a mutual interaction between the vanes occurs after the vortex pairing. The reconnection from the four sectors vortices induces a significant increase of azimuthal vorticity, which affects the dynamical behaviour of the precessing vortex core. The latter is visualized by a low-order spatio-temporal reconstruction based on few dynamical modes. At a higher swirl number ($S\geqslant 0.6$), the axial vorticity component dominates the flow field; it interacts with the azimuthal vorticity, which penetrates inward through the meanders of the vane wakes and forces the vortex core precession and breakdown.

Spatio-temporal image-based parametric water surface reconstruction: a novel methodology based on refraction

This paper presents a low-cost and easy-to-implement image-based reconstruction technique for laboratory experiments, which results in a temporal description of the water surface topography. The distortion due to refraction of a known pattern, located below the water surface, is used to fit a low parameter surface model that describes the time-dependent and three-dimensional surface variation. Instead of finding the optimal water depth for characteristic points on the surface, the deformation of the entire pattern is compared to its original shape. This avoids the need for feature tracking adopted in similar techniques, which improves the robustness to suboptimal optical conditions and small-scale, high-frequency surface perturbations. Experimental validation, by comparison with water depth measurements using a level gauge and pressure sensor, proves sub-millimetre accuracy for smooth and steady surface shapes. Although such accuracy cannot be achieved in case of highly dynamic surface phenomena, the low-frequency and large-scale free surface oscillations can still be measured with a temporal and spatial resolution mostly limited by the available optical set-up. The technique is initially intended for periodic surface phenomena, but the results presented in this paper indicate that also irregular surface shapes can robustly be reconstructed. Therefore, the presented technique is a promising tool for other research applications that require non-intrusive, low-cost surface measurements while maintaining visual access to the water below the surface. The latter ensures that the suggested surface reconstruction is compatible with simultaneous image-based velocity measurements, enabling a detailed study of the flow.

Buildup dynamics of dissipative soliton in an ultrafast fiber laser with net-normal dispersion.

Taking advantage of technology of spatio-temporal reconstruction and dispersive Fourier transform (DFT), we experimentally observed the buildup dynamics of dissipative soliton in an ultrafast fiber laser in the net-normal dispersion regime. The soliton buildup dynamics were analyzed in both the spectral and temporal domains. We firstly revealed that the appearing of the spectral sharp peaks with oscillation structures during the mode-locking transition is caused by the formation of structural dissipative soliton. The experimental results were explained by the numerical simulations. These findings would give some new insights into the dissipative soliton buildup dynamics in ultrafast fiber lasers.