Search Results (24)

While sensing in high temporal resolution is necessary for a wide range of applications, it is still limited nowadays due to the camera sampling rate. In this work, we try to increase the temporal resolution beyond the Nyquist frequency, which is limited by the sensor’s sampling rate. This work establishes a novel approach to temporal super-resolution that uses the object-reflecting properties from an active illumination source to go beyond this limit. Following theoretical derivation and the development of signal-processing-based algorithms, we demonstrate how to increase the detected temporal spectral range by a factor of six and possibly even more. Our method is supported by simulations and experiments, and we demonstrate (via application) how we use our method to dramatically improve the accuracy of object motion estimation. We share our simulation code on GitHub. Full article

The transient electromagnetic method (TEM) is widely used in the exploration of mineral, petroleum, and geothermal resources due to its sensitivity to low-resistivity bodies, limited site constraints, and strong resistance to interference. In practical applications, the TEM often uses a long wire source instead of an idealized horizontal electric dipole (HED) source as the excitation source. This is due to the complex external conditions and the relatively large distance between the receiving zone and the transmitter source. Compared to the HED, the long wire source can provide a larger excitation current, generating stronger signals to meet the requirements of a higher signal-to-noise ratio or deeper exploration. It also produces longer-duration signals, thereby providing better resolution. Additionally, for the interpretation of TEM data, three-dimensional forward modeling plays a crucial role. However, the mature traditional TEM forward method is based on a simple, sometimes inappropriate model, as it is well established that the induced polarization (IP) effect is widely present in the deep earth, especially in oil and gas reservoirs. The presence of the IP effect results in negative responses in field data that do not conform to the traditional theoretical decay law of TEM, which can significantly impact data processing and inversion results. To address this issue, a TEM forward modeling method considering the IP effect based on the spectral element method (SEM) has been developed in this study. Firstly, starting from the Helmholtz equation satisfied by the time domain electric field, we introduce the Debye model with polarization information into the forward modeling by utilizing the differential form of Ohm’s law. As a result, we derive the boundary value problem for the time domain electric field that considers the induced polarization effect. Using Gauss–Lobatto–Legendre (GLL) polynomials as the basis functions, the SEM is employed to discretize the governing equations at each time step and obtain spectral element discretization equations. Then, temporal discretization equations are derived using the second-order backward Euler formula, and the linear system of equations is solved using the Pardiso direct solver. Finally, the electromagnetic responses at any time channel are obtained via SEM interpolation and numerical integration, thereby achieving three-dimensional TEM forward modeling considering the IP effect. The results indicate that this method can effectively reflect the spatial distribution of polarizable subsurface media. It provides valuable references for studying the polarization parameters of subsurface media and performing a three-dimensional inversion of TEM data considering the induced polarization effect. Full article

The optimal selection of characteristic bands and retrieval models for the hyperspectral retrieval of soil heavy metal concentrations poses a significant challenge. Additionally, satellite-based hyperspectral retrieval encounters several issues, including atmospheric effects, limitations in temporal and radiometric resolution, and data acquisition, among others. Given this, the retrieval performance of the soil arsenic (As) concentration in Pingtan Island, the largest island in Fujian Province and the fifth largest in China, is currently unclear. This study aimed to elucidate this issue by identifying optimal characteristic bands from the full spectrum from both statistical and physical perspectives. We tested three linear models, namely Multiple Linear Regression (MLR), Partial Least Squares Regression (PLSR) and Geographically Weighted Regression (GWR), as well as three nonlinear machine learning models, including Back Propagation Neural Network (BP), Support Vector Machine Regression (SVR) and Random Forest Regression (RFR). We then retrieved soil arsenic content using ground-based soil full spectrum data on Pingtan Island. Our results indicate that the RFR model consistently outperformed all others when using both original and optimal characteristic bands. This superior performance suggests a complex, nonlinear relationship between soil arsenic concentration and spectral variables, influenced by diverse landscape factors. The GWR model, which considers spatial non-stationarity and heterogeneity, outperformed traditional models such as BP and SVR. This finding underscores the potential of incorporating spatial characteristics to enhance traditional machine learning models in geospatial studies. When evaluating retrieval model accuracy based on optimal characteristic bands, the RFR model maintained its top performance, and linear models (MLR, PLSR and GWR) showed notable improvement. Specifically, the GWR model achieved the highest r value for the validation data, indicating that selecting optimal characteristic bands based on high Pearson’s correlation coefficients (e.g., abs(Pearson’s correlation coefficient) ≥0.45) and high sensitivity to soil active materials successfully mitigates uncertainties linked to characteristic band selection solely based on Pearson’s correlation coefficients. Consequently, two effective retrieval models were generated: the best-performing RFR model and the improved GWR model. Our study on Pingtan Island provides theoretical and technical support for monitoring and evaluating soil arsenic concentrations using satellite-based spectroscopy in densely populated, relatively independent island towns in China and worldwide. Full article

Ultrafast electron diffraction (UED) is a powerful tool for observing the evolution of transient structures at the atomic level. However, temporal resolution is a huge challenge for UEDs, mainly depending on the pulse duration. Unfortunately, the Coulomb force between electrons causes the pulse duration to increase continually when propagating, reducing the temporal resolution. In this paper, we theoretically design a radio frequency (RF) compression cavity using the finite-element method of electromagnetic–thermal coupling to overcome this limitation and obtain a high-brightness, short-pulse-duration, and stable electron beam. In addition, the cavity’s size parameters are optimized, and a water-cooling system is designed to ensure stable operation. To the best of our knowledge, this is the first time that the electromagnetic–thermal coupling method has been used to study the RF cavity applied to UED. The results show that the RF cavity operates in TM010 mode with a resonant frequency of 2970 MHz and generates a resonant electric field. This mode of operation generates an electric field that varies periodically and transiently, compressing the electronic pulse duration. The electromagnetic–thermal coupling method proposed in this study effectively improves the temporal resolution of UED. Full article

Though microscopy is most often intended as a technique for providing qualitative assessment of cellular and subcellular properties, when coupled with other instruments such as wavelength selectors, lasers, photoelectric devices and computers, it can perform a wide variety of quantitative measurements, which are demanding in establishing relationships between the properties and structures of biological material in all their spatial and temporal complexities. These combinations of instruments are a powerful approach to improve non-destructive investigations of cellular and subcellular properties (both physical and chemical) at a macromolecular scale resolution. Since many subcellular compartments in living cells are characterized by structurally organized molecules, this review deals with three advanced microscopy techniques well-suited for these kind of investigations, i.e., microspectrophotometry (MSP), super-resolution localization microscopy (SRLM) and holotomographic microscopy (HTM). These techniques can achieve an insight view into the role intracellular molecular organizations such as photoreceptive and photosynthetic structures and lipid bodies play in many cellular processes as well as their biophysical properties. Microspectrophotometry uses a set-up based on the combination of a wide-field microscope and a polychromator, which allows the measurement of spectroscopic features such as absorption spectra. Super resolution localization microscopy combines dedicated optics and sophisticated software algorithms to overcome the diffraction limit of light and allow the visualization of subcellular structures and dynamics in greater detail with respect to conventional optical microscopy. Holotomographic microscopy combines holography and tomography techniques into a single microscopy set-up, and allows 3D reconstruction by means of the phase separation of biomolecule condensates. This review is organized in sections, which for each technique describe some general aspects, a peculiar theoretical aspect, a specific experimental configuration and examples of applications (fish and algae photoreceptors, single labeled proteins and endocellular aggregates of lipids). Full article

Peatlands provide vital ecosystem and carbon services, and Canada is home to a significant peatland carbon stock. Global climate warming trends are expected to lead to increased carbon release from peatlands, as a consequence of drought and wildfire. Monitoring hydrologic regimes is a key in understanding the impacts of warming, including monitoring changes in small and temporally variable water bodies in peatlands. Global surface water mapping has been implemented, but the spatial and temporal scales of the resulting data products prevent the effective monitoring of peatland water bodies, which are small and prone to rapid hydrologic changes. One hurdle in the quest to improve remote-sensing-derived global surface water map quality is the omission of small and temporally variable water bodies. This research investigated the reasons for small peatland water body omission as a preparatory step for surface water mapping, using Sentinel-1 SAR data and image classification methods. It was found that Sentinel-1 backscatter signatures for small peatland water bodies differ from large water bodies, due in part to differing physical characteristics such as waves and emergent vegetation, and limitations in detectable feature sizes as a result of SAR image processing and resolution. The characterization of small peatland water body backscatter provides a theoretical basis for the development of SAR-based surface water mapping methods with high accuracy for our purposes of wildfire susceptibility monitoring in peatlands. This study discusses the implications of small peatland water body omission from surface water maps on carbon, climate, and hydrologic models. Full article

The delay caused by the troposphere is one of the major sources of errors limiting the accuracy of InSAR measurements. The tropospheric correction of InSAR measurements is important. The Weather Research and Forecasting (WRF) Model is a state-of-the-art mesoscale numerical weather prediction system designed for atmospheric research applications. It can be applied to InSAR tropospheric correction. Its parameters can be altered according to the requirements of the given application. WRF is usually initialized based on 3 h- or 6 h temporal resolution data in InSAR tropospheric correction studies, a lower temporal resolution compared to ERA5 data. A lower time resolution means a longer integration time for WRF to simulate from the initial time to the target time. Initialization with a higher resolution can shorten the integration time of the simulation theoretically and improve its accuracy. However, an evaluation of the effectiveness of ERA5_WRF for InSAR tropospheric correction is lacking. To evaluate the efficiency of WRF tropospheric correction, we used Reanalysis v5 (ERA5) from the European Centre for Medium-Range Weather Forecasts (ECMWF) for initialization to drive the WRF (ERA5_WRF) for efficient applications in InSAR. Three methods based on global atmospheric models—FNL_WRF (tropospheric correction method based on WRF driven by NCEP FNL), Generic Atmospheric Correction Online Service for InSAR (GACOS), and ERA5—were used to evaluate the corrective effects of ERA5_WRF. The reliability of ERA5_WRF in different scenarios with large tropospheric delay was evaluated from the spatial and temporal perspectives by considering seasonal, topographic, and climatic factors. Its applications in the local space showed that ERA5_WRF could adequately correct tropospheric delay. Benefits include its high-quality data sources and the simulation of WRF, and its application in different seasons had proven superior to other methods in terms of the corrective effects of elevation-related and spatially related delays in summer. By analyzing the data sources and downscaling methods of correction methods and weather conditions of cases, ERA5_WRF had superior performance under the condition of large content and hourly variation of tropospheric delay. Furthermore, WRF showed the potential for tropospheric correction when other higher-quality data appear in the future. Full article

Geno- and phenotypic heterogeneity amongst cancer cell subpopulations are established drivers of treatment resistance and tumour recurrence. However, due to the technical difficulty associated with studying such intra-tumoural heterogeneity, this phenomenon is seldom interrogated in conventional cell culture models. Here, we employ a fluorescent lineage technique termed “optical barcoding” (OBC) to perform simultaneous longitudinal tracking of spatio-temporal fate in 64 patient-derived colorectal cancer subclones. To do so, patient-derived cancer cell lines and organoids were labelled with discrete combinations of reporter constructs, stably integrated into the genome and thus passed on from the founder cell to all its clonal descendants. This strategy enables the longitudinal monitoring of individual cell lineages based upon their unique optical barcodes. By designing a novel panel of six fluorescent proteins, the maximum theoretical subpopulation resolution of 64 discriminable subpopulations was achieved, greatly improving throughput compared with previous studies. We demonstrate that all subpopulations can be purified from complex clonal mixtures via flow cytometry, permitting the downstream isolation and analysis of any lineages of interest. Moreover, we outline an optimized imaging protocol that can be used to image optical barcodes in real-time, allowing for clonal dynamics to be resolved in live cells. In contrast with the limited intra-tumour heterogeneity observed in conventional 2D cell lines, the OBC technique was successfully used to quantify dynamic clonal expansions and contractions in 3D patient-derived organoids, which were previously demonstrated to better recapitulate the heterogeneity of their parental tumour material. In summary, we present OBC as a user-friendly, inexpensive, and high-throughput technique for monitoring intra-tumoural heterogeneity in in vitro cell culture models. Full article

Solute tracer tests are an established method for the characterization of flow and transport processes in fractured rock. Such tests are often monitored with borehole sensors which offer high temporal sampling and signal to noise ratio, but only limited spatial deployment possibilities. Ground penetrating radar (GPR) is sensitive to electromagnetic properties, and can thus be used to monitor the transport behavior of electrically conductive tracers. Since GPR waves can sample large volumes that are practically inaccessible by traditional borehole sensors, they are expected to increase the spatial resolution of tracer experiments. In this manuscript, we describe two approaches to infer quantitative hydrological data from time-lapse borehole reflection GPR experiments with saline tracers in fractured rock. An important prerequisite of our method includes the generation of GPR data difference images. We show how the calculation of difference radar breakthrough curves (DRBTC) allows to retrieve relative electrical conductivity breakthrough curves for theoretically arbitrary locations in the subsurface. For sufficiently small fracture apertures we found the relation between the DRBTC values and the electrical conductivity in the fracture to be quasi-linear. Additionally, we describe a flow path reconstruction procedure that allows computing approximate flow path distances using reflection GPR data from at least two boreholes. From the temporal information during the time-lapse GPR surveys, we are finally able to calculate flow-path averaged tracer velocities. Our new methods were applied to a field data set that was acquired at the Grimsel Test Site in Switzerland. DRBTCs were successfully calculated for previously inaccessible locations in the experimental rock volume and the flow path averaged velocity field was found to be in good accordance with previous studies at the Grimsel Test Site. Full article

The theoretical temporal resolution limit $t_T$ of a silicon photodiode (Si PD) is 11.1 ps. We call “super temporal resolution” the temporal resolution that is shorter than that limit. To achieve this resolution, Germanium is selected as a candidate material for the photodiode (Ge PD) for visible light since the absorption coefficient of Ge for the wavelength is several tens of times higher than that of Si, allowing a very thin PD. On the other hand, the saturation drift velocity of electrons in Ge is about 2/3 of that in Si. The ratio suggests an ultra-short propagation time of electrons in the Ge PD. However, the diffusion coefficient of electrons in Ge is four times higher than that of Si. Therefore, Monte Carlo simulations were applied to analyze the temporal resolution of the Ge PD. The estimated theoretical temporal resolution limit is 0.26 ps, while the practical limit is 1.41 ps. To achieve a super temporal resolution better than 11.1 ps, the driver circuit must operate at least 100 GHz. It is thus proposed to develop, at first, a short-wavelength infrared (SWIR) ultra-high-speed image sensor with a thicker and wider Ge PD, and then gradually decrease the size along with the progress of the driver circuits. Full article

Land surface temperature (LST) is an important variable in the physics of land–surface processes controlling the heat and water fluxes over the interface between the Earth’s surface and the atmosphere. Space-borne remote sensing provides the only feasible way for acquiring high-precision LST at temporal and spatial domain over the entire globe. Passive microwave (PMW) satellite observations have the capability to penetrate through clouds and can provide data under both clear and cloud conditions. Nonetheless, compared with thermal infrared data, PMW data suffer from lower spatial resolution and LST retrieval accuracy. Various methods for estimating LST from PMW satellite observations were proposed in the past few decades. This paper provides an extensive overview of these methods. We first present the theoretical basis for retrieving LST from PMW observations and then review the existing LST retrieval methods. These methods are mainly categorized into four types, i.e., empirical methods, semi-empirical methods, physically-based methods, and neural network methods. Advantages, limitations, and assumptions associated with each method are discussed. Prospects for future development to improve the performance of LST retrieval methods from PMW satellite observations are also recommended. Full article

A broadband energy-chirped hard X-ray pulse has been demonstrated at the SwissFEL (free electron laser) with up to 4% bandwidth. We consider the characteristic parameters for analyzing the time dependence of stationary protein diffraction with energy-chirped pulses. Depending on crystal mosaic spread, convergence, and recordable resolution, individual reflections are expected to spend at least ≈ 50 attoseconds and up to ≈ 8 femtoseconds in reflecting condition. Using parameters for a chirped XFEL pulse obtained from simulations of 4% bandwidth conditions, ray-tracing simulations have been carried out to demonstrate the temporal streaking across individual reflections and resolution ranges for protein crystal diffraction. Simulations performed at a higher chirp (10%) emphasize the importance of chirp magnitude that would allow increased observation statistics for the temporal separation of individual reflections for merging and structure determination. Finally, we consider the fundamental limitation for obtaining time-dependent observations using chirped pulse diffraction. We consider the maximum theoretical time resolution achievable to be on the order of 50–200 as from the instantaneous bandwidth of the chirped SASE pulse. We then assess the ability to propagate ultrafast optical pulses for pump-probe cross-correlation under characteristic conditions of material dispersion; in this regard, the limiting factors for time resolution scale with crystal thickness. Crystals that are below a few microns in size will be necessary for subfemtosecond time resolution. Full article

Slow waves (SWs) are spatio-temporal patterns of cortical activity that occur both during natural sleep and anesthesia and are preserved across species. Even though electrophysiological recordings have been largely used to characterize brain states, they are limited in the spatial resolution and cannot target specific neuronal population. Recently, large-scale optical imaging techniques coupled with functional indicators overcame these restrictions, and new pipelines of analysis and novel approaches of SWs modelling are needed to extract relevant features of the spatio-temporal dynamics of SWs from these highly spatially resolved data-sets. Here we combined wide-field fluorescence microscopy and a transgenic mouse model expressing a calcium indicator (GCaMP6f) in excitatory neurons to study SW propagation over the meso-scale under ketamine anesthesia. We developed a versatile analysis pipeline to identify and quantify the spatio-temporal propagation of the SWs. Moreover, we designed a computational simulator based on a simple theoretical model, which takes into account the statistics of neuronal activity, the response of fluorescence proteins and the slow waves dynamics. The simulator was capable of synthesizing artificial signals that could reliably reproduce several features of the SWs observed in vivo, thus enabling a calibration tool for the analysis pipeline. Comparison of experimental and simulated data shows the robustness of the analysis tools and its potential to uncover mechanistic insights of the Slow Wave Activity (SWA). Full article

The accuracy of thin-film characterization in terahertz spectroscopy is mainly set by the thickness uncertainty. Physical thickness measurement has limited accuracy for thin-film samples thinner than a few hundreds of micrometers and is sometimes even impossible. The temporal resolution of time-domain terahertz spectrometers is not sufficient to resolve such thin films. Previously reported numerical methods mainly only work for materials with low dispersion and absorption. Here, we propose a novel method for thickness determination by fitting a non-inflection offset exponential function to the material optical properties. Theoretical analysis predicts the best fitting to only be achieved when the correct thickness is given. Transmission measurements on a thin-film polymer, water, and a lactose pallet verify the theory and show the accurate thickness determination and property characterization on materials which are either achromatic or dispersive, transparent or absorptive, featureless or resonant. The measurements demonstrate the best versatility and sensitivity compared to the state-of-art. The method could be widely adapted to various types of research and industrial applications. Full article

Light in flight was captured by a single shot of a newly developed backside-illuminated multi-collection-gate image sensor at a frame interval of 10 ns without high-speed gating devices such as a streak camera or post data processes. This paper reports the achievement and further evolution of the image sensor toward the theoretical temporal resolution limit of 11.1 ps derived by the authors. The theoretical analysis revealed the conditions to minimize the temporal resolution. Simulations show that the image sensor designed following the specified conditions and fabricated by existing technology will achieve a frame interval of 50 ps. The sensor, 200 times faster than our latest sensor will innovate advanced analytical apparatuses using time-of-flight or lifetime measurements, such as imaging TOF-MS, FLIM, pulse neutron tomography, PET, LIDAR, and more, beyond these known applications. Full article