Temporal Resolution Research Articles

A novel optimization-assisted multi-scale and dilated adaptive hybrid deep learning network with feature fusion for event detection from social media

ABSTRACT Social media networks become an active communication medium for connecting people and delivering new messages. Social media can perform as the primary channel, where the globalized events or instances can be explored. Earlier models are facing the pitfall of noticing the temporal and spatial resolution for enhancing the efficacy. Therefore, in this proposed model, a new event detection approach from social media data is presented. Firstly, the essential data is collected and undergone for pre-processing stage. Further, the Bidirectional Encoder Representations from Transformers (BERT) and Term Frequency Inverse Document Frequency (TF-IDF) are employed for extracting features. Subsequently, the two resultant features are given to the multi-scale and dilated layer present in the detection network of GRU and Res-Bi-LSTM, named as Multi-scale and Dilated Adaptive Hybrid Deep Learning (MDA-HDL) for event detection. Moreover, the MDA-HDL network’s parameters are tuned by Improved Gannet Optimization Algorithm (IGOA) to enhance the performance. Finally, the execution of the system is done over the Python platform, where the system is validated and compared with baseline methodologies. The accuracy findings of model acquire as 94.96 for dataset 1 and 96.42 for dataset 2. Hence, the recommended model outperforms with the superior results while detecting the social events.

A greedy regularized block Kaczmarz method for accelerating reconstruction in magnetic particle imaging

Objective. Magnetic particle imaging (MPI) is an emerging medical tomographic imaging modality that enables real-time imaging with high sensitivity and high spatial and temporal resolution. For the system matrix reconstruction method, the MPI reconstruction problem is an ill-posed inverse problem that is commonly solved using the Kaczmarz algorithm. However, the high computation time of the Kaczmarz algorithm, which restricts MPI reconstruction speed, has limited the development of potential clinical applications for real-time MPI. In order to achieve fast reconstruction in real-time MPI, we propose a greedy regularized block Kaczmarz method (GRBK) which accelerates MPI reconstruction. Approach. GRBK is composed of a greedy partition strategy for the system matrix, which enables preprocessing of the system matrix into well-conditioned blocks to facilitate the convergence of the block Kaczmarz algorithm, and a regularized block Kaczmarz algorithm, which enables fast and accurate MPI image reconstruction at the same time. Main results. We quantitatively evaluated our GRBK using simulation data from three phantoms at 20 dB, 30 dB, and 40 dB noise levels. The results showed that GRBK can improve reconstruction speed by single orders of magnitude compared to the prevalent regularized Kaczmarz algorithm including Tikhonov regularization, the non-negative Fused Lasso, and wavelet-based sparse model. We also evaluated our method on OpenMPIData, which is real MPI data. The results showed that our GRBK is better suited for real-time MPI reconstruction than current state-of-the-art reconstruction algorithms in terms of reconstruction speed as well as image quality. Significance. Our proposed method is expected to be the preferred choice for potential applications of real-time MPI.

Computational modeling for the quantitative assessment of cardiac autonomic response to orthostatic stress.

The Autonomic Nervous System (ANS) plays a critical role in regulating cardiac functions. Early detection of ANS dysfunctions is crucial for preventing or slowing the progression of cardiovascular diseases. Current methods for analyzing ANS activity, such as heart rate variability analysis and muscle sympathetic nerve activity recording, face challenges such as poor temporal resolution, invasiveness, and insufficient sensitivity to individual physiological variations, which limit personalized health assessments. This study aims to introduce the open-loop Mathematical Model of Autonomic Regulation of the Cardiac System under Supine-to-stand Maneuver (MMARCS) to overcome the limitations of existing ANS analysis methods. The MMARCS model is designed to offer a balance between physiological fidelity and simplicity, focusing on the ANS cardiac control subsystems' input-output curve. The MMARCS model simplifies the complex internal dynamics of ANS cardiac control by emphasizing input-output relationships and utilizing sensitivity analysis and parameter subset selection to increase model specificity and eliminate redundant parameters. This approach aims to enhance the model's capacity for personalized health assessments. The application of the MMARCS model revealed significant differences in ANS regulation between healthy (14 females and 19 males) and diabetic subjects (8 females and 6 males). Parameters indicated heightened sympathetic activity and diminished parasympathetic response in diabetic subjects compared to healthy subjects (p<0.05), and also suggested a more sensitive and potentially more reactive sympathetic response among diabetic subjects (p<0.05). The MMARCS model represents an innovative computational approach for quantifying ANS functionality, offering potential benefits for clinical measurements of cardiovascular, disease progression monitoring, and home health monitoring via wearable technology. Its balance between physiological accuracy and model simplicity makes it a promising tool for personalized health assessments.

High-Speed Imaging and Quantitative Analysis of Non-Equilibrium Stochastic Processes Using Atomic-Resolution Electron Microscopy

Abstract Chemical phenomena are inherently complex and stochastic, making them difficult to fully understand using conventional ensemble-averaged analytical methods. These methods primarily capture long-lived species and common structural features, limiting the study of transient intermediates and minute structural characteristics. In contrast, single-molecule time-resolved analysis using advanced microscopy techniques, particularly transmission electron microscopy (TEM), offers high spatial and temporal resolution to observe the nonequilibrium dynamics of molecules and their assemblies. This account discusses the authors’ research on developing TEM techniques to visualize intricate and transient interactions within molecular systems, enhancing the understanding of chemical phenomena at atomic and molecular levels.

Capturing cell morphology dynamics with high temporal resolution using single-shot quantitative phase gradient imaging.

Label-free quantitative phase imaging can potentially measure cellular dynamics with minimal perturbation, motivating efforts to develop faster and more sensitive instrumentation. We characterize fast, single-shot quantitative phase gradient microscopy (ss-QPGM) that simultaneously acquires multiple polarization components required to reconstruct phase images. We integrate a computationally efficient least squares algorithm to provide real-time, video-rate imaging (up to ). The developed instrument was used to observe changes in cellular morphology and correlate these to molecular measures commonly obtained by staining. We aim to characterize a fast approach to ss-QPGM and record morphological changes in single-cell phase images. We also correlate these with biochemical changes indicating cell death using concurrently acquired fluorescence images. Here, we examine nutrient deprivation and anticancer drug-induced cell death in two different breast cell lines, viz., M2 and MCF7. Our approach involves in-line measurements of ss-QPGM and fluorescence imaging of the cells biochemically labeled for viability. We validate the accuracy of the phase measurement using a USAF1951 pattern phase target. The ss-QPGM system resolves , and our analysis scheme accurately retrieves the phase with a high correlation coefficient ( ), as measured by calibrated sample thicknesses. Analyzing the contrast in phase, we estimate the spatial resolution achievable to be for this microscope. ss-QPGM time-lapse live-cell imaging reveals multiple intracellular and morphological changes during biochemically induced cell death. Inferences from co-registered images of quantitative phase and fluorescence suggest the possibility of necrosis, which agrees with previous findings. Label-free ss-QPGM with high-temporal resolution and high spatial fidelity is demonstrated. Its application for monitoring dynamic changes in live cells offers promising prospects.

Searching for axion forces with spin precession in atoms and molecules

We propose to use atoms and molecules as quantum sensors of axion-mediated monopole-dipole forces. We show that electron spin precession experiments using atomic and molecular beams are well-suited for axion searches thanks to the presence of co-magnetometer states and single-shot temporal resolution. Experimental strategies to detect axion gradients from localised sources and the earth are presented, taking ACME III as a prototype example. Other possibilities including atomic beams, and laser-cooled atoms and molecules are discussed.

Acoustic phonon excitation in gold probed by time-resolved photoemission electron microscopy.

Electron-phonon coupling is an important energy transfer mechanism in solids after ultrafast laser excitation. In this study, we present an extreme ultraviolet (EUV) and infrared (IR) pump-probe photoemission experiment to investigate the electron-phonon coupling in nonequilibrium gold. The energy of IR-laser-emitted photoelectrons is shifted due to the EUV photoemission and oscillates with a ∼4THz frequency. Such oscillation is considered as the effective excitation of the longitudinal acoustic phonon mode in gold through the spectral-dependent electron-phonon coupling. Our study showcases the capability of time-resolved photoemission electron microscopy to monitor the non-equilibrium lattice vibrations with ultrahigh spatial and temporal resolution.

Succession and seasonality of a Brazilian secondary tropical dry forest: Phenology and climate moderation

With large tracts of Tropical Dry Forests (TDF) in the Americas previously deforested, many places are currently undergoing secondary ecological succession. These processes vary in time and space, creating a landscape with forests of different ages or successional stages. These secondary forests need moreneed more understanding about how their ecosystem functionality is restored and recovering along the succession path. In particular, it is poorly understood how different successional stages moderate extremes of Essential Climatic Variables (ECV) such as temperature, relative humidity, soil moisture, and the fraction of Absorbed Photosynthetic Active Radiation (fAPAR). This paper, therefore, studies the linkages between high temporal resolution tower-based optical canopy phenology time series and seasonal changes in local ECV conditions between early (10–12 years) and late (50+ years) successional stage TDF in southeastern Brazil. We compare diurnal and seasonal patterns of understory ECVs between early/late plots and investigate the canopy’s Climate Moderating Capacity (CMC). Our data indicate at least 100 mm of precipitation within two weeks is necessary to initiate leaf flushing in this TDF. We also find that soil moisture and daytime air humidity strongly correlate (R2 > 0.75) with seasonal patterns in canopy vegetation greenness indices and fAPAR with a cross-correlation time lag peak of 12–15 days. Our results suggest that the late stage is more effective at cooling (−1.4 ± 0.6 °C vs −0.8 ± 0.6 °C) and reducing daytime evaporation (−0.41 ± 0.2 kPa vs −0.18 ± 0.12 °C) in the understory during the growing season than the early stage. Results suggest that the CMC varies with seasonal canopy leaf area dynamics and with heat and moisture scales, becoming significantly stronger when temperatures and vapour pressure deficits were highest, and correlated strongly with canopy fAPAR dynamics (R2 = 0.82). These findings demonstrate that TDFs can effectively regain microclimatic buffering capacity.

An algorithm to analyse long‐term tendencies of pressure systems over Europe

AbstractClimate change is associated with the modification of the polar jet stream, cyclone tracks and corresponding circulation patterns over midlatitudes. To apply these synoptic changes on regional climate, the changing sensitivity of a specific location to different pressure centre regions must be studied. An automated, objective circulation pattern detection method was developed to investigate the evolution of cyclonic and anticyclonic influence at any specific point within the European domain. The algorithm was used to assign each location to influencing low‐ or high‐pressure centres within the domain. Pressure centre displacements and the frequency redistribution among different centres were studied for each location. The 180‐year (January 1836–December 2015) mean sea level pressure dataset on the European domain with a 0.703° × 0.702° spatial and daily temporal resolution was obtained from NOAA 20th Century Reanalysis project. The presented method can apply the continental‐scale changes to specific locations. A significant increase of anticyclonic influence was found in southern and central Europe, in line with the northward displacement of Atlantic cyclones. Hundred and eighty year (180‐year) change of the number of days with anticyclonic versus cyclonic influence was found to be between +10% and 15% in the Mediterranean and +2% and 10% in most of Europe. The increasing anticyclonic influence in central Europe was strongest in the spring and the winter and was most attributable to the eastern European anticyclone. Results highlight the importance of research on the dynamical climate response of anticyclonic pressure systems.

High-throughput physiological phenotyping of crop evapotranspiration at the plot scale

ContextPlatforms and instrumentation for Field High-Throughput Plant Phenotyping (FHTPP) are well developed to measure important traits for crop breeding and agronomic studies. However, the research has focused on morphological and spectral traits; and approaches to estimate major physiological processes such as evapotranspiration (ET) for small experimental plots are lacking. ObjectiveIn this study, we put forward a new analytical framework to estimate plot-scale ET by integrating frequent phenotyping data (multispectral and thermal infrared images, canopy reflectance, and LiDAR point clouds) from a FHTPP system (known as NU-Spidercam), the weather data, a simplified two-source energy balance model, and reference ET and crop coefficient calculation. MethodsThe new plot-scale ET method was tested on five field experiments involving maize and soybean crops over two growing seasons, with the different treatment levels of irrigation water. Estimated plot-scale ET was accumulated across the growing reason for each plot, and its association with grain yield was investigated with regression analysis. ResultsThe result showed that plot-scale accumulated ET captured the seasonal trend of plot water use and clearly differentiated the irrigation treatments. Strong linear correlations were observed between plot-scale ET and grain yield, with R2 values ranging from 0.35 to 0.93 (average R2 = 0.71). Plot-scale ET appeared to be a more steady and stronger predictor of grain yield across the seasons than several other morphological and spectral traits including crop height, green pixel fraction, canopy temperature depression, and red-edge normalized difference vegetation index. ConclusionHigh spatial and temporal resolution of the field phenotyping data, along with the new analytical framework reported, successfully estimated ET at small plot scale, which is difficult to achieve with other systems or methods. SignificancesOur work of estimating ET at the plot-scale can be adopt to other ground-based platforms and drones, thus empowers physiologists, breeders, and agronomists for high-throughput phenotyping of water-use related traits and drought response evaluation.

Tracing Opioids Across the US: A High-Resolution Pharmaceutical Distribution Dataset

In the field of pharmaceutical supply chains, there is a lack of comprehensive historical data, representing a significant barrier to advancing research. To address this gap, we introduce a high-resolution dataset comprising drug packages distributed to approximately 300,000 pharmacies, hospitals, and practitioners across the US. We reconstruct 375 million distribution paths from ARCOS, a DEA-maintained database comprising half a billion shipping records between 2006 and 2014. While ARCOS tracks dyadic shipments, it does not provide information on the complete journey of single packages from manufacturers to final destinations. Our algorithm is able to reconstruct complete distribution paths from these dyadic records. The reconstructed dataset, with its high temporal and spatial resolution, offers an unprecedented view of US pharmaceutical distribution and is a valuable resource for investigating supply and distribution networks.

Effect of Tropical Cyclone Wind Forcing on Improving Upper Ocean Simulation: An Idealized Study

We examined how wind forcing affects the upper ocean response under idealized tropical cyclone (TC) conditions. In this study, we constructed three parameterized wind fields with varying spatial and temporal resolutions for TCs of different intensities and translation speeds. The simulated surface and subsurface temperatures were cooler and deeper when using the blended wind fields owing to their higher wind speeds compared to those from coarse–resolution wind fields. Additionally, TC–induced currents were significantly stronger on the right side of the TC track, with notable differences in current velocities. Similar to the increase in ocean currents, the simulated turbulent kinetic energy driven by the blended winds is significantly higher than that simulated by the coarse-resolution wind fields. These findings suggest that using high-quality wind fields to drive ocean models can enhance the accuracy of the upper ocean response to TCs. The sensitivity of the upper ocean responses to wind forcing depends on the TC’s intensity and translation speed. Stronger and slower-moving TCs induce greater vertical shear and enhanced mixing. Therefore, accurate wind stress as a surface boundary condition is crucial for numerical ocean models.

A light-efficient and versatile multiplexing method for snapshot spectral imaging

The study of rapid and stochastic events that involve multiple species, such as chemical reactions and plasma dynamics, requires means to capture multispectral information in two dimensions at both high temporal- and spatial resolution. Commercially available cameras that provide high temporal resolution are based on either signal intensification or rapid data acquisition. Intensified cameras provide extremely short acquisition times using intensification by means of micro channel plates, but the conversion between electrons and photons makes these cameras inherently monochrome. In contrast, high-speed cameras can achieve color-sensitivity through integrated Bayer filters but suffer from a reduced light collection efficiency and a fixed spectral composition. In this article we present a non-integrated optical arrangement for instantaneous multispectral imaging based on FRAME image multiplexing. By spectrally separating the signal using lossless dichroic mirrors, a 16-fold increase in light-collection efficiency is gained (compared to past solutions), resulting in an equivalent increase in temporal resolution. This improvement provides new avenues for multispectral imaging of rapid events. We demonstrate the system’s versatility and suitability for studies of such processes by applying it for (i) temperature mapping using a high-resolution CCD camera, (ii) high-speed videography up to 10 kHz at four spectral channels and (iii) dual-species visualization in a plasma discharge using an intensified sCMOS camera.

Spatio-Temporal Behavior of Land Surface Temperatures (LSTs) in Central Chile, Using Terra MODIS Images

Land surface temperature (LST) is one of the most important variables in the physical processes of surface energy and water balance. The temporal behavior of LST was analyzed between the latitudes 32°00′ S and 34°24′ S (Valparaíso and Metropolitana regions of Chile) for three summer months (December, January, and February) in the 2000–2017 period, using the Terra MODIS image information and applying the Mann–Kendall test. The results show an increase in LST in the study area, particularly in the Andes mountain range in January (5240 km2), which mainly comprises areas devoid of vegetation and eternal snow and glaciers, and are zones that act as water reserves for the capital city of Santiago. Similarly, vegetated areas such as forests, grasslands, and shrublands also show increasing trends in LST but over smaller surfaces. Because this study is regional, it is recommended to improve the spatial and temporal resolutions of the images to obtain conclusions on more local scales.

Tidal and seasonal influence on cold seep activity and methanotroph efficiency in the North Sea

The ocean’s methane emission to the atmosphere is dominated by continental shelves where cold seeps are globally common features. Seeps emit methane into the hydrosphere, but temporal variations and controls of seep activity and the efficiency of the microbial methane filter in the water column are scarce. Here we address these knowledge gaps by measuring whole water column methane inventories and methanotrophic activity at a temporal resolution of 2 hours at a North Sea cold seep (Doggerbank) in summer and autumn. We found that bottom water methane inventories were 68% (summer) and 11% (autumn) higher during low tide compared to high tide coinciding with increased methanotrophic activity. The activity of methanotrophs was reduced during autumn when the water column was fully mixed and matched by higher methane emissions to the atmosphere. Our results show that tides are underappreciated controls on seepage and methanotrophic activity and methane sea–atmosphere fluxes.

Direct flipping dynamics and quantized enrichment of chirality at single-molecule resolution.

Chirality is an important aspect of nature, and numerous macroscopic methods have been developed to understand and control chirality. For the chiral tertiary amines, their flexible flipping process makes it possible to achieve high chiral controllability without bond formation and breaking. Here, we present a type of stable chiral single-molecule devices formed by tertiary amines, using graphene-molecule-graphene single-molecule junctions. These single-molecule devices allow real-time, in situ, and long-time measurements of the flipping process of an individual chiral nitrogen center with high temporal resolution. Temperature- and bias voltage-dependent experiments, along with theoretical investigations, revealed diverse chiral intermediates, indicating the regulation of the flipping dynamics by energy-related factors. Angle-dependent measurements further demonstrated efficient enrichment of chiral states using linearly polarized light by a symmetry-related factor. This approach offers a reliable means for understanding the chirality's origin, elucidating microscopic chirality regulation mechanisms, and aiding in the design of effective drugs.

Monitoring and analyzing the dynamics of Zizania floating mats with PlanetScope imagery and Google Earth Engine

Zizania latifolia has been observed to generate floating mats due to water level fluctuations and wind-waves, leading to significant detrimental impacts on both water quality and biodiversity. The key to controlling and monitoring the spread and movement of Zizania floating is the early detection of outbreaks and the clarification of its formation mechanisms in response to water levels and wind actions. The temporal and spatial resolutions of conventional remote sensing monitoring methods are challenging to satisfy the requirements for continuous and accurate tracking of Zizania floating, which undergoes daily movement. This study develops a timely and accurate monitoring method for Zizania floating by calculating the Normalized Difference Vegetation Index (NDVI) from high spatiotemporal resolution PlanetScope (PS) imagery and building a decision tree on the Google Earth Engine (GEE) platform. Taking the Zizania floating outbreak in Honghu Wetland as the subject of our study, we extracted the continuous movement trajectories of Zizania floating from May to September 2019. Subsequently, we analyzed the interrelationship between the formation of Zizania floating and hydrometeorological factors. We then investigated the effects of Zizania floating on water quality and biodiversity. The results show that: (1) The integration of PS imagery and the GEE platform holds the potential to simplify the workload of remote sensing data processing. Based on the difference in NDVI between water bodies and Zizania floating, the dynamic expansion and reduction areas of the Zizania floating were successfully extracted by setting the threshold at 0.3, enabling timely and accurate tracking. (2) Abrupt fluctuations in water levels during brief time intervals serve as the primary trigger for Zizania floating. Additionally, wind speed during the same timeframe acts as a catalyst for the emergence of Zizania floating, with wind direction influencing its movement. (3) The outbreak of Zizania floating significantly elevates the concentrations of total nitrogen (TN), total phosphorus (TP), chemical oxygen demand (CODmn), and total ammonia nitrogen (TAN), while concurrently reducing the dissolved oxygen (DO) concentration in water bodies. The prolonged presence and movement of Zizania floating has reduced the biodiversity of the wetland ecosystem. Zizania floating mats present unique challenges due to their unpredictability, complicating the monitoring and tracking processes. It is necessary to develop a prompt, accurate, and cost-effective detection program for Zizania floating to reduce the risk it poses to wetland ecosystems.

Plant life-history data as evidence of an historical mixed-severity fire regime in Banksia Woodlands

Context The concept of the fire regime is central to understanding and managing fire-prone ecosystems globally, and information on past regimes can provide useful insights into species disturbance adaptations. Although observations from satellite imagery or palaeoecological proxy data can provide direct evidence of past, pre-colonial fire regimes, they may be limited in temporal or spatial resolution and are not available for all ecosystems. However, fire-related plant-trait and demographic data offer an alternative approach to understand species–fire regime associations at the ecosystem scale. Aims We aimed to quantify the life-history strategies and associated fire regimes for six co-occurring shrub and tree species from fire-prone, Mediterranean-climate Banksia Woodlands in south-western Australia. Methods We collected static demographic data on size structure, seedling recruitment, and plant mortality across sites of varying time since last fire. We combined demographic data with key fire-related species traits to define plant life-history strategies. We then compared observed life histories with a priori expectations for surface, stand-replacing, and mixed-severity fire-regime types to infer historical fire-regime associations. Key results Fire-killed shrubs and weakly serotinous trees had abundant post-fire seedling recruitment, but also developed multi-cohort populations during fire-free periods via inter-fire seedling recruitment. Resprouting shrubs had little seedling recruitment at any time, even following fire, and showed no signs of decline in the long absence of fire, likely owing to their very long lifespans. Conclusions The variation in life-history strategies for these six co-occurring species is consistent with known ecological strategies to cope with high variation in fire intervals in a mixed-severity fire regime. Whereas resprouting and strong post-fire seedling recruitment indicate a tolerance of shorter fire intervals, inter-fire recruitment and weak serotiny are interpreted as a bet-hedging strategy to cope with occasional long fire-free periods that may otherwise exceed adult and seed-bank lifespans. Implications Our findings suggested that Banksia Woodlands have evolved with highly variable fire intervals in a mixed-severity fire regime. Further investigations of species adaptations to varying fire size and patchiness can help extend our understanding of fire-regime tolerances.

Formation of diffuse and spark discharges between two needle electrodes with the scattering of particles

The development of a nanosecond discharge in a pin-to-pin gap filled with air at atmospheric pressure has been studied with high temporal and spatial resolutions from a breakdown start to the spark decay. Positive and negative nanosecond voltage pulses with an amplitude of tens of kilovolts were applied. Time-resolved images of the discharge development were taken with a four-channel Intensified Charge Coupled Device (ICCD) camera. The minimum delay between the camera channels could be as short as ≈ 0.1 ns. This made it possible to study the gap breakdown process with subnanosecond resolution. It was observed that a wide-diameter streamer develops from the high-voltage pointed electrode. The ionization processes near the grounded pin electrode started when the streamer crossed half of the gap. After bridging the gap by the streamer, a diffuse discharge was formed. The development of spark leaders from bright spots on the surface of the pointed electrodes was observed at the next stage. It was found that the rate of development of the spark leader is an order of magnitude lower than that of the wide-diameter streamer. Long thin luminous tracks were observed against the background of a discharge plasma glow. It has been established that the tracks are adjacent to brightly glowing spots on the electrodes and are associated with the flight of small particles.

Energy-Resolving Time-of-Flight Mass Spectrometry for Bulk Plasma Analysis.

This work presents a newly designed energy-resolving time-of-flight mass spectrometer (E-TOFMS) for analysing the energy and mass of ions in bulk plasma. The system comprises an electrostatic sector analyser (ESA) for energy-to-charge (E/Q) ratio resolution and an orthogonal reflectron TOFMS for mass-to-charge (m/Q) ratio analysis. The design choices are explained, providing insight into electron and ion path simulations. The instrument was characterised using various ion generation sources, including an electron impact ion source, high power impulse magnetron sputtering, and microwave plasma electron cyclotron resonance sources. To validate its functionality, the energy-resolving data was compared with data obtained under the same conditions using a Langmuir probe and a retarding field energy analyser (RFEA). The benefits of the proposed E-TOFMS were demonstrated by sputtering highly alloyed steel with multiple isotope-rich elements, such as Mo or W. This technique offers an E/Q ratio resolution of up to 0.15 V for a range up to 125 V and a m/Q ratio resolution of at least 700 Th for a range up to 250 Th, with a temporal resolution of 10 μs.