Temporal Resolution Research Articles

Continuous surface-to-distributed acoustic sensor snapshots explain reactivation of individual natural fractures during an unconventional reservoir stimulation

Fiber-optic sensing technologies allow petroleum engineering teams to detect hydraulic fracture interaction with boreholes during unconventional reservoir stimulation. In combination with high-repeatability seismic sources, the same distributed acoustic sensors (DASs) enable vertical seismic profiling (VSP) of the fracture evolution away from the boreholes. We discovered clear signatures of seismic scattering on activated fractures during nine days of continuous seismic monitoring of the fracturing stages at the Austin Chalk/Eagle Ford Field Laboratory. The present study applies a novel approach for quantitative analysis of the scattering events in terms of the evolution of the geometry and elastic stiffness of individual fractures. Our characterization strategy sequentially refines the fracture models: from a stack of 1D soft layers to 3D rectangular inclusions. First, we estimate the number of fracture locations and reflectivity using a modified sparse-spike deconvolution of the stacked VSP traces. The fracture set consists of five fractures spaced by 15–30 m with a reflectivity of approximately 1%. Then, we develop a scattering integral method to refine these estimates along with an inversion of the fracture top and bottom for each monitoring vintage. We find that, initially, some of the fractures are located above the monitoring fiber with the height of approximately 100 m. Then we integrate the seismic interpretation with the low-frequency DAS and pressure and microseismic monitoring to reconstruct the activation process of the fractures. Most likely, some of the natural fractures slowly grew downward to the monitoring fiber as a result of fluid injections in the stimulated well. This led to bright strain anomalies but did not trigger seismicity. The top of the fractures remained almost constant and were limited by a lithologic boundary/stress barrier. To our knowledge, this is the first time VSP data enabled tracking of the fracture evolution with such high spatial and temporal resolution, which was previously only available for crosswell surveys and at a much smaller scale.

MRI and CT compatible asymmetric bilayer hydrogel electrodes for EEG-based brain activity monitoring

The exploration of multi-dimensional brain activity with high temporal and spatial resolution is of great significance in the diagnosis of neurological disease and the study of brain science. Although the integration of electroencephalogram (EEG) with magnetic resonance imaging (MRI) and computed tomography (CT) provides a potential solution to achieve a brain-functional image with high spatiotemporal resolution, the critical issues of interface stability and magnetic compatibility remain challenging. Therefore, in this research, we proposed a conductive hydrogel EEG electrode with an asymmetrical bilayer structure, which shows the potential to overcome the challenges. Benefiting from the bilayer structure with different moduli, the hydrogel electrode exhibits high biological and mechanical compatibility with the heterogeneous brain-electrode interface. As a result, the impedance can be reduced compared with conventional metal electrodes. In addition, the hydrogel-based ionic conductive electrodes, which are free from metal conductors, are compatible with MRI and CT. Therefore, they can obtain high spatiotemporal resolution multi-dimensional brain information in clinical settings. The research outcome provides a new approach for establishing a platform for early diagnosis of brain diseases and the study of brain science.

Sub-20-fs UV-XUV beamline for ultrafast molecular spectroscopy

We present an ultraviolet (UV) - extreme-ultraviolet (XUV) pump-probe beamline with applications in ultrafast time-resolved photoelectron spectroscopy. The UV pump pulses, tuneable between 255 and 285 nm and with µJ-level energy, are generated by frequency up-conversion between ultrashort visible/infrared pulses and visible narrow-band pulses. Few-femtosecond XUV probe pulses are produced by a high-order harmonic generation source equipped with a state-of-the-art time-delay compensated monochromator. Two-colour UV-XUV sidebands are used for a complete in situ temporal characterization of the pulses, demonstrating a temporal resolution of better than 20 fs. We validate the performances of the beamline through a UV-XUV pump-probe measurement on 1,3-cyclohexadiene, resolving the ultrashort dynamics of the first conical intersection. This instrument opens exciting possibilities for investigating ultrafast UV-induced dynamics of organic molecules in ultrashort time scales.

Three-Dimensional (3D) Flood Simulation Aids Informed Decision Making: A Case of a Two-Story Underground Parking Lot in Beijing

Flooding in underground spaces, such as subway stations, underground malls, and garages, has increased due to intensified rainfall, urbanization, and population growth. Traditional 2D simulations often overlook crucial vertical flow variations, especially in steep transitions like stairs and ramps. The current study aims to investigate the flood dynamics in large underground geometries by taking a parking lot in Beijing, China, as a study case. The model overcomes the limitations of previous simulations by adapting a full 3D mesh-based simulation with reasonable computational cost. Unlike earlier studies, this model employs a high temporal resolution transient inflow at the inlet to the underground space. Simulation scenarios consider different return periods (5, 20, and 100 years) and inlet water depths, providing an analysis of their impact on flood status in the underground structure. The model generates high spatial–temporal results, enabling precise detection of flood-prone locations, evacuation times, and suggested mitigation techniques. The results recommend evacuating from hazard areas before the 10th minute during extreme flood events. Additionally, the study estimates a 40% increase in flood hazards for scenarios with direct connections between levels. Overall, the study highlights the importance of 3D simulations for accurate risk assessment.

Combining low- and high-frequency microwave radiometer measurements from the MOSAiC expedition for enhanced water vapour products

Abstract. In the central Arctic, high-quality water vapour observations are sparse due to the low density of meteorological stations and uncertainties in satellite remote sensing. Different reanalyses also disagree on the amount of water vapour in the central Arctic. The Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition provides comprehensive observations that are suitable for evaluating satellite products and reanalyses. Radiosonde observations provide high-quality water vapour estimates with a high vertical but a low temporal resolution. Observations from the microwave radiometers (MWRs) on board the research vessel Polarstern complement these observations through high temporal resolution. In this study, we demonstrate the high accuracy of the combination of the two MWRs HATPRO (Humidity and Temperature Profiler) and MiRAC-P (Microwave Radiometer for Arctic Clouds – Passive). For this purpose, we developed new retrievals of integrated water vapour (IWV) and profiles of specific humidity and temperature using a neural network approach, including observations from both HATPRO and MiRAC-P to utilize their different water vapour sensitivity. The retrievals were trained with the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5) and synthetic MWR observations simulated with the Passive and Active Microwave radiative TRAnsfer tool (PAMTRA). We applied the retrievals to synthetic and real observations and evaluated them with ERA5 and radiosondes launched during MOSAiC, respectively. To assess the benefit of the combination of HATPRO and MiRAC-P compared to single MWR retrievals, we compared the errors with respect to MOSAiC radiosondes and computed the vertical information content of the specific humidity profiles. The root mean squared error (RMSE) of IWV was reduced by up to 15 %. Specific humidity biases and RMSE were reduced by up to 75 % and 50 %, respectively. The vertical information content of specific humidity could be increased from 1.7 to 2.4 degrees of freedom. We also computed relative humidity from the retrieved temperature and specific humidity profiles and found that RMSE was reduced from 45 % to 15 %. Finally, we show a case study demonstrating the enhanced humidity profiling capabilities compared to the standard HATPRO-based retrievals. The vertical resolution of the retrieved specific humidity profiles is still low compared to radiosondes, but the case study revealed the potential to resolve major humidity inversions. To what degree the MWR combination detects humidity inversions, also compared to satellites and reanalyses, will be part of future work.

The future of quantum technologies for brain imaging.

The neurosciences have pioneered the use of quantum technologies for sensing and imaging the brain. Next-generation technologies promise routes towards low-cost, wearable imaging devices with high spatial and temporal resolution.

The acoustic complexity index (ACI): theoretical foundations, applied perspectives and semantics

The acoustic complexity index (ACI) is a commonly used metric in ecoacoustics, demonstrating reliability across diverse environments and ecological conditions. However, this index requires specific procedures to be applied correctly. Based on the Canberra metric, the ACI is an unsupervised metric formulated to extract information from fast Fourier transform (FFT) sonic matrices. The ACI measures contiguous differences in acoustic energy of each frequency bin along temporal steps (ACItf) and a temporal interval along the frequency bins (ACIft). Aggregating data after an FFT with a clumping procedure allows for better scaling of sonic signals before computing the ACI. A filter must be applied to reduce the effects of nonenvironmental signals produced by microphone electrical noise . Due to the singularity of the index for values of 0, ACI requires ad hoc procedures to exclude element pairs for which one of the elements is equal to 0 from the comparisons. The spectral and temporal sonic signatures are vectors obtained from the sequence of ACItf and ACIft values, respectively. The comparison between sonic signatures using the chord distance index returns spectral and temporal sonic dissimilarities, allowing the evaluation of sonic patterns at different temporal and spatial resolutions. Sonic variability, sonic evenness, and the effective number of frequency bins are further derivative metrics that help interpret sonic heterogeneity by distinguishing the temporal and spatial heterogeneity of sonoscapes. Moreover, this paper proposes changing the terminology of ‘acoustic complexity index' to ‘sonic heterogeneity index.'

High-resolution modeling and projection of heat-related mortality in Germany under climate change

Abstract Heat is a leading cause of premature deaths during summer months. Understanding the relationship between high temperatures and excess mortality is crucial for designing effective prevention and adaptation plans. Traditional statistical methods have been repeatedly applied to analyze heat-related mortality. However, spatially and temporally high-resolution analyses are challenging due to fragmented data archives across different agglomeration levels, especially for mortality data. We propose a neural network-based model to estimate heat-related mortality. This approach allows for high temporal and spatial resolution estimations, such as regional heat risk during specific heatwaves. Using Germany as a case study, we calculated heat-related excess mortality rates at the district level and visualized the dynamics of local health risks within a heatwave. Overall, we estimated a total of 48,000 heat-related deaths in Germany over the last decade (2014-2023), with most occurring during specific heatwave events. For example, in 2023, the heatwave from July 7-14 contributed approximately 28% (1100 deaths) to the total of about 3,900 heat-related deaths for the entire year. This estimation is consistent with previously published reports from the Robert Koch Institute (RKI), considering the resolution differences in the input data. In addition, we combined our model with shared socio-economic pathways (SSPs) of future climate change, assuming a static population and baseline mortality rate. The results suggest that heat-related risk in Germany could further increase by a factor of 2.5 (SSP245) to 9 (SSP370) without adaptation to extreme heat. Our approach is a valuable tool for the monitoring of regional heat-related risks as well as scenario-based risks projections for the future. The results of the model can help develop climate-driven public health strategies, aiding in the identification of local risks during heatwaves and in long-term resilience planning. Key messages • High-resolution modeling of heat-related mortality helps us to develop targeted adaptation and prevention plans. • The majority of heat-related mortality occurs during heatwaves in summer.

Artificial Tactile Sensory Finger for Contact Pattern Identification Based on High Spatiotemporal Piezoresistive Sensor Array.

Human fingertip tactile perception relies on the activation of densely distributed tactile receptors to identify contact patterns in the brain. Despite significant efforts to integrate tactile sensors with machine learning algorithms for recognizing physical patterns on object surfaces, developing a tactile sensing system that emulates human fingertip capabilities for identifying contact patterns with a high spatiotemporal resolution remains a formidable challenge. In this study, we present the development of an artificial tactile finger for accurate contact pattern identification, achieved through the integration of a high spatiotemporal piezoresistive sensor array (PRSA) and a convolutional neural network (CNN) model. Spatiotemporal characterization tests reveal that the artificial finger exhibits a fast temporal resolution of approximately 7 ms and achieves a two-point threshold of 1.5 mm, surpassing that of the human fingertip. To compare the performance of the artificial finger with the human finger in recognizing different patterns, we acquired pressure images by pressing the artificial finger, coated with a flexible PRSA film, onto both simple embossed and complex curved patterns while also recording human recognition results of perceiving these patterns. Experimental findings demonstrate that the artificial finger achieves higher classification accuracy in recognizing both simple and complex patterns (99.0 and 96.1%, respectively) compared to the human fingertip (69.1 and 22.7%). This artificial finger serves as a promising platform with great potential for various robotic tactile sensing applications including prosthetics, skin electronics, and robotic surgery.

Identification of left ventricular flow features in healthy and pathological conditions

Abstract Background In the presence of mitral valve diseases or following surgical interventions, the hemodynamics in the left ventricle (LV) are significantly altered [1]. These maladaptive intraventricular hemodynamic alterations can stimulate a cascade of events leading to progressive adverse LV remodeling and eventual heart failure [2]. Qualitative and quantitative evaluation of LV flow features may provide a potential for sensitive risk stratification of clinical cardiac function [3]. Purpose The purpose of this study is to identifying LV flow features using in vitro experiments under both normal and pathological conditions, including mitral regurgitation (MR), mitral valve replacement with bioprosthetic/mechanical valve, and transcatheter mitral valve edge-to-edge repair (TEER). Methods We utilized a biohybrid approach to construct the in vitro experimental platform, where the native mitral valve (including chordae tendineae and papillary muscles) and aortic valve from porcine were combined with a 3D-printed silicon LV (figure 1). To ensure comparability across different conditions, we maintained consistency by utilizing the same native valve and 3D-printed LV. For pathological conditions, we cut the chordae tendineae in A2 zone to induce the severe degenerative MR, and TEER was performed on this prolapsed valve by placing two clips in A2-P2 zone. Then, the anterior leaflet of valve was cut, and a bioprosthetic valve and mechanical valve were sutured to mitral annulus to simulate surgical valve replacement, respectively. Left ventricular flow fields were measured using four-dimensional particle image velocimetry (4D-PIV) technique, with vector interval of 0.9 mm in all the spatial directions and temporal resolution of 10 ms. Results Significant differences in mean flow field were observed among healthy and pathological conditions (figure 2). Firstly, the vortex orientation was clockwise in healthy, MR, bioprosthetic valve replacement, and TEER conditions, which could accompany the redirection of blood flows towards the aortic valve. However, the replacement with a mechanical valve resulted in an alteration in vortex orientation from clockwise to counterclockwise. Secondly, the position of the center of the vortex changed in pathological conditions, with the center of the vortex closest to the apex and the left ventricle outflow tract in the healthy condition. Thirdly, the maximum Reynolds shear stress (RSS), which may be responsible for thrombus formation, significantly increased after TEER procedure and bioprosthetic valve replacement. Conclusions This study demonstrates significant changes in LV hemodynamics across different conditions. The flow features, including vortex orientations, vortex positions and the RSS, may potentially become crucial considerations for the optimization of artificial valves and mitral valve repair devices.Figure 1 Figure 2

Prediction of the Relative Resource Abundance of the Argentine Shortfin Squid Illex argentinus in the High Sea in the Southwest Atlantic Based on a Deep Learning Model

To analyze the impact of the marine environment on the relative abundance of Illex argentinus (high and low categories) in the southwest Atlantic, this study collected logbook data from Chinese pelagic trawlers from December 2014 to June 2024, including vessel position data and oceanographic variables such as sea surface temperature, 50 m and 100 m water temperature, sea surface salinity, sea surface height, chlorophyll-a concentration, and mixed layer depth. Vessel positions were used to enhance the logbook data quality, allowing an analysis of the annual trends in the resource center of this squid at a spatial resolution of 0.1° × 0.1° and a temporal resolution of ten days. The findings showed that the resource center is primarily located around 42° S in the north and between 45° S and 47° S in the south, with a trend of northward movement during the study period. Additionally, we constructed two ensemble learning models based on decision trees—AdaBoost and PSO-RF—aiming to identify the most critical environmental factors that affect its resource abundance; we found that the optimal model was the PSO-RF model with max_depth of 5 and n_estimators of 46. The importance analysis revealed that sea surface temperature, mixed layer depth, sea surface height, sea surface salinity, and 50 m water temperature are critical environmental factors affecting this species’ resources. Given that deep learning models generally have shorter running times and higher accuracy than other models, we developed a CNN-Attention model based on the five most important input factors. This model achieved an accuracy of 73.6% in forecasting this squid for 2024, predicting that the population would first appear near the Argentine exclusive economic zone around mid-December 2023 and gradually move east and south thereafter. The predictions of the model, validated through log data, maintained over 70% accuracy during most periods at a time scale of ten days. The successful construction of the resource abundance forecasting model and its accuracy improvements can help enterprises save fuel and time costs associated with blind searches for target species. Moreover, this research contributes to improving resource utilization efficiency and reducing fishing duration, thereby aiding in lowering carbon emissions from pelagic trawling activities, offering valuable insights for the sustainable development of this species’ resources.

Disruption Dynamics and Charge Transfer of a Single Attoliter Emulsion Droplet Revealed by Combined Fast-Scan Sinusoidal Voltammetry and Short Time Fourier Transform Analysis.

Single-entity electrochemistry has gained significant attention for the analysis of individual cells, nanoparticles, and droplets, which is leveraged by robust electrochemical techniques such as chronoamperometry and cyclic voltammetry (CV) to extract information about single entities, including size, kinetics, mass transport, etc. For an in-depth understanding such as dynamic interaction between the electrode and a single entity, the unconventional fast electrochemical technique is essential for time-resolved analysis. This fast experimental technique is unfortunately hindered by a substantial nonfaradaic response. In this work, we introduce fast-scan sinusoidal voltammetry (FSSV) combined with a short-time Fourier transform (STFT) for analyzing single emulsion droplets. Utilizing ultramicroelectrode and fast potential sweeps up to apparent 200 V/s, we achieved high temporal resolution (8 ms per voltammogram) to capture the current signals during droplet collisions. STFT analysis reveals the amplitude and phase changes, allowing for the accurate detection of collision events even in the absence of redox species. By adopting an algorithm of drift-free baseline subtraction, a conventional CV shape was obtained in FSSV. The reacted charge from the single-entity voltammogram at every 8 ms was also plotted. This method effectively addresses limitations in traditional techniques, providing insights into emulsion dynamics such as droplet contact and droplet breakdown.

Temporally resolved growth patterns reveal novel information about the polygenic nature of complex quantitative traits.

Plant height can be an indicator of plant health across environments and used to identify superior genotypes. Typically plant height is measured at a single timepoint when plants reach terminal height. Evaluating plant height using unoccupied aerial vehicles allows for measurements throughout the growing season, facilitating a better understanding of plant-environment interactions and the genetic basis of this complex trait. To assess variation throughout development, plant height data was collected from planting until terminal height at anthesis (14 flights 2018, 27 in 2019, 12 in 2020, and 11 in 2021) for a panel of ~500 diverse maize inbred lines. The percent variance explained in plant height throughout the season was significantly explained by genotype (9-48%), year (4-52%), and genotype-by-year interactions (14-36%) to varying extents throughout development. Genome-wide association studies revealed 717 significant single nucleotide polymorphisms associated with plant height and growth rate at different parts of the growing season specific to certain phases of vegetative growth. When plant height growth curves were compared to growth curves estimated from canopy cover, greater Fréchet distance stability was observed in plant height growth curves than for canopy cover. This indicated canopy cover may be more useful for understanding environmental modulation of overall plant growth and plant height better for understanding genotypic modulation of overall plant growth. This study demonstrated that substantial information can be gained from high temporal resolution data to understand how plants differentially interact with the environment and can enhance our understanding of the genetic basis of complex polygenic traits.

Comparison of whole-brain task-modulated functional connectivity methods for fMRI task connectomics

Higher brain functions require flexible integration of information across widely distributed brain regions depending on the task context. Resting-state functional magnetic resonance imaging (fMRI) has provided substantial insight into large-scale intrinsic brain network organisation, yet the principles of rapid context-dependent reconfiguration of that intrinsic network organisation are much less understood. A major challenge for task connectome mapping is the absence of a gold standard for deriving whole-brain task-modulated functional connectivity matrices. Here, we perform biophysically realistic simulations to control the ground-truth task-modulated functional connectivity over a wide range of experimental settings. We reveal the best-performing methods for different types of task designs and their fundamental limitations. Importantly, we demonstrate that rapid (100 ms) modulations of oscillatory neuronal synchronisation can be recovered from sluggish haemodynamic fluctuations even at typically low fMRI temporal resolution (2 s). Finally, we provide practical recommendations on task design and statistical analysis to foster task connectome mapping.

Characterization of hydrometeorological events and flood impacts in the Basque Country

Abstract. In this study, the focus is on the characterization of floods in Basque Autonomous Community, considering damages, hydrometeorological aspects and others factors during the period 2000–2021. The ultimate goal is to contribute to understanding the processes of impact, enhancing awareness, and improving preparedness before flood events. To assess flood impact, damage data from the Spanish Insurance Compensation Consortium areexposureccccccc used as a proxy. For hydro-meteorological characterization and weather context, we use data from the Automatic Weather Station Network and various Euskalmet general and local ad-hoc weather context classifications. Different datasets are conveniently prepared to extract a range of indicators, taking into account: (1) physiographic and socio-economic factors, (2) damages and impact, (3) hydrometeorological aspects, and (4) weather context. Visual data analytics techniques are utilized for analysis, characterization, and presentation of findings. We integrate indicators with diverse temporal resolutions (daily and monthly) and spatial aggregations (primary watersheds and selected hydrological units) to facilitate discussions and derive conclusions. This work establishes a foundation for a semi-automatic procedure for data preparation, indicator extraction, analysis, and results presentation. Although it is a strategy specifically designed for its application in our context, we believe it can serve as inspiration for conducting similar free software based exercises in other parts of the world.

A Continuous and Noninvasive Method to Estimate Pao2/Fio2 Ratio.

To validate a method for continuously estimating the Pao2/Fio2 (PF) ratio in all critically ill pediatric patients using only standard continuous data monitoring. Retrospective study on a high temporal resolution database. PICU in Montreal, QC, Canada. We included any patients admitted from May 2015 to May 2023 who had an arterial blood gas (ABG) with concurrent continuous pulsed oximetry saturation (Spo2) values. We used our previously validated mathematical model to determine the magnitude of hypoxemia by computing the estimated ePao2/Fio2 (ePF) ratio and comparing it to the Spo2/Fio2 (SF), using PF ratio as the reference standard. None. We analyzed a total of 20,828 ABGs. When Spo2 was below or equal to 97%, the ePF ratio showed a significantly better hypoxemia classification (none, light/moderate, or severe) than the SF ratio (0.80 vs. 0.72; p < 0.001), a lower fixed bias (16.26 vs. -35.24; p < 0.001), a lower mean absolute error (37.92 vs. 63.93; p < 0.001) and a lower proportional bias (slope of 1.01 vs. 0.81; p < 0.001). ePF ratio has also a better limits of agreement difference from Bland-Altman plot (248.10 vs. 292.45; p < 0.001) and coefficient of determination (0.68 vs. 0.59; p < 0.001). When Spo2 was above 97%, the ePF ratio had better classification with Kappa (0.53 vs. 0.43; p < 0.001) and lower fixed bias (-0.63 vs. 65.68; p < 0.001). The PF ratio based on ePF allows for a continuous estimation of hypoxemia severity with a better performance than the SF ratio.

Embodied Semantics: Early Simultaneous Motor Grounding in First and Second Languages

Background/Objectives: Although the embodiment of action-related language is well-established in the mother tongue (L1), less is known about the embodiment of a second language (L2) acquired later in life through formal instruction. We used the high temporal resolution of ERPs and topographic ERP analyses to compare embodiment in L1 and L2 and to investigate whether L1 and L2 are embodied with different strengths at different stages of linguistic processing. Methods: Subjects were presented with action-related and non-action-related verbs in a silent reading task. Subjects were late French–German and German–French bilinguals, respectively, and we could therefore collapse across languages to avoid common confounding between language (French and German) and order of acquisition (L1, L2). Results: We could show distinct effects of embodiment and language. Embodiment affected only the sensory and lexical stages of processing with increased strength and power of the N1 component for motor vs. non-motor verbs, and language affected the lexical and semantic stages of processing with stronger P2/N400 components for L2 than for L1. Non-motor verbs elicited a stronger P1 component in L2. Conclusions: Our results suggest that processing words in L2 requires more effortful processing. Importantly, L1 and L2 are not embodied differently, and embodiment affects early and similar stages of processing in L1 and L2, possibly integrating other process of action–language interaction

Visualization of commuting areas and examination of jobs-housing balance with the adoption of excess commuting

Rapid urban growth extends the boundaries of urbanized areas and makes people spend extra travel cost on the journey to work. Scholars have examined commuting behaviors between residence and work places within a region, and suggested the conceptual theory of jobs-housing balance to evaluate if there are sufficient job opportunities for residents in the region. A quantitative measurement of excess commuting is proposed to reflect the degree of jobs-house balance. However, current studies focus on the evaluation of excess commuting and the causality of spatial restructuring between residence and workplace, the spatial extend of excess commuting in an urban region is not visually delineated. In addition, conventional studies acquire static data such as statistic data or other survey data to analyze impacts of commuting patterns on urban formation. Today the emergence of spatial big data sheds light on the causality of urban commuting from higher spatial and temporal resolutions. This study aims to examine the degree of jobs-housing balance through the calculation of excess commuting and represent the spatial extent of excess commuting of Taichung metropolitan area in Taiwan. Electronic Toll Collection (ETC) data, the spatial big data which is publicly accessible in Taiwan, is introduced as the commuting data and to calculate three key parameters of excess commuting, Tmin, Tobs, and Tmax. The three parameters are used to visualize the extent of commuting zones and examine commuting patterns of Taichung metropolitan area and observe the spatial relationship between those patterns and land-use types. The evaluation of excess commuting indicates that the degree of jobs-housing imbalance in Taichung metropolitan area is similar to Los Angeles metropolis in US. The analytical results explain how ETC data can be successfully used for the calculation of excess commuting, and visualization of the extent of commuting regions. In addition, after the cluster analysis of residential areas, it is intuitive to observe spatial correlation between hot zones of residential areas and the spatial extent of theoretical maximum commuting, and shows that the scenarios of commuting can be considered as an indicator to explain the possibility of urban expansion in the future.

Microfabrication Technologies for Nanoinvasive and High-Resolution Magnetic Neuromodulation.

The increasing demand for precise neuromodulation necessitates advancements in techniques to achieve higher spatial resolution. Magnetic stimulation, offering low signal attenuation and minimal tissue damage, plays a significant role in neuromodulation. Conventional transcranial magnetic stimulation (TMS), though noninvasive, lacks the spatial resolution and neuron selectivity required for spatially precise neuromodulation. To address these limitations, the next generation of magnetic neurostimulation technologies aims to achieve submillimeter-resolution and selective neuromodulation with high temporal resolution. Invasive and nanoinvasive magnetic neurostimulation are two next-generation approaches: invasive methods use implantable microcoils, while nanoinvasive methods use magnetic nanoparticles (MNPs) to achieve high spatial and temporal resolution of magnetic neuromodulation. This review will introduce the working principles, technical details, coil designs, and potential future developments of these approaches from an engineering perspective. Furthermore, the review will discuss state-of-the-art microfabrication in depth due to its irreplaceable role in realizing next-generation magnetic neuromodulation. In addition to reviewing magnetic neuromodulation, this review will cover through-silicon vias (TSV), surface micromachining, photolithography, direct writing, and other fabrication technologies, supported by case studies, providing a framework for the integration of magnetic neuromodulation and microelectronics technologies.

Dilation framing camera with the dual-pulse excitation technique

In an inertial confinement fusion (ICF) ultrafast diagnostic system that is based on electron beam time-dilation, an ultrafast electrical pulse is used to excite a microstrip photocathode (PC), which generates a varying PC voltage to obtain a photoelectron velocity that varies with emission time. The photoelectron beam achieves time-dilation through the drift process and is then detected by a time-resolved sensor, thereby increasing the temporal resolution of the diagnostic system. A pulse time-dilation diagnostic system is simulated, while the sensor is a gated microchannel plate (MCP) detector with a temporal resolution of 100 ps and an excitation pulse on a PC with a slope of 3 V/ps; the diagnostic system achieves a temporal resolution of 11.12 ps. However, the excitation pulse creates a voltage difference across the PC. A voltage difference of 900 V can be acquired for a PC length of 60 mm, which yields a nonuniform spatial resolution ranging from 30.4 µm to approximately 3000 µm. Furthermore, the voltage difference across the PC also limits the frame size to 2.2 mm along the pulse propagation direction according to the simulation results. To achieve a uniform spatial resolution and a larger frame size, a dual-pulse excitation technique on a PC is presented, which is the technique to symmetrically apply voltage pulses at both ends of the PC microstrip. The theoretical results show that this technique will improve the uniformity of the PC voltage spatial distribution. When the PC pulse slope is 3 V/ps and the dual-pulse excitation technique is employed, the diagnostic system has a temporal resolution of 5.91 ps and a uniform spatial resolution of 30.4 µm. Furthermore, the frame size along the pulse propagation direction is improved to the effective length of the microstrip PC.