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1. Volume averaging effect in nonlinear processes of focused laser fields

   Yao, Yuzhong Freund (September 2021, Journal of chemical physics)

   null (Ed.)

   We report theoretical derivations and experimental results on the volume averaging effect of nonlinear processes in focused laser fields. This effect is considered detrimental in revealing the intensity dependence of a nonlinear process, caused by the intensity variation across the sampled volume of a focused laser. Following the treatment in the literature, we prove that if the signal dependence can be expressed as a simple power function of the laser intensity and if the detection region encompasses effectively the whole volume, volume average does not affect the final conclusion on the derived exponent. However, to reveal the detailed saturation effect of a multi-photon process, intensity selective scans involving spatial filters and displacement of the laser focus (z-scan) are required. Moreover, to fully capture the dependence of the signal on the variation of the laser intensity, the degree of spatial discrimination and the corresponding range of z-scan need to be modeled carefully. Limitations in the dynamic range of the detector or the laser power, however, can thwart the desired scan range, resulting in erroneous fitting exponents. Using our nanosecond laser with a non-ideal Gaussian beam profile, based on multiphoton ionization of argon atoms from a collimated molecular beam and from ambient argon gas, we report experimental measurements of the beam waist and Rayleigh range, and compare the experimental intensity dependence of Ar+ with theoretical values. Agreements between theory and experiment are remarkable. 

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2. Terrestrial Laser Scan Metrics Predict Surface Vegetation Biomass and Consumption in a Frequently Burned Southeastern U.S. Ecosystem

   https://doi.org/10.3390/fire6040151  

   Loudermilk, Eva Louise; Pokswinski, Scott; Hawley, Christie M.; Maxwell, Aaron; Gallagher, Michael R.; Skowronski, Nicholas S.; Hudak, Andrew T.; Hoffman, Chad; Hiers, John Kevin (April 2023, Fire)

   Fire-prone landscapes found throughout the world are increasingly managed with prescribed fire for a variety of objectives. These frequent low-intensity fires directly impact lower forest strata, and thus estimating surface fuels or understory vegetation is essential for planning, evaluating, and monitoring management strategies and studying fire behavior and effects. Traditional fuel estimation methods can be applied to stand-level and canopy fuel loading; however, local-scale understory biomass remains challenging because of complex within-stand heterogeneity and fast recovery post-fire. Previous studies have demonstrated how single location terrestrial laser scanning (TLS) can be used to estimate plot-level vegetation characteristics and the impacts of prescribed fire. To build upon this methodology, co-located single TLS scans and physical biomass measurements were used to generate linear models for predicting understory vegetation and fuel biomass, as well as consumption by fire in a southeastern U.S. pineland. A variable selection method was used to select the six most important TLS-derived structural metrics for each linear model, where the model fit ranged in R2 from 0.61 to 0.74. This study highlights prospects for efficiently estimating vegetation and fuel characteristics that are relevant to prescribed burning via the integration of a single-scan TLS method that is adaptable by managers and relevant for coupled fire–atmosphere models. 

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3. ScanCloud: Holistic GPR Data Analysis for Adaptive Subsurface Object Detection

   https://doi.org/10.1109/IRI51335.2021.00027  

   Omwenga, Maxwell M.; Wu, Dalei; Liang, Yu; Huston, Dryver; Xia, Tian (August 2021, 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science (IRI))

   The conventional ground penetrating radar (GPR) data analysis methods, which use piecemeal approaches in processing the GPR data formulated in variant formats such as A-Scan, B-Scan, and C-Scan, fail to provide a global view of underground objects on the fly to adapt the operations of GPR systems in the field. To bridge the gap, in this paper, we propose a novel GPR data analysis approach termed “ScanCloud” which is focused on the whole in situ GPR dataset rather than on individual A-Scans, B-Scans or C-Scans. We also study the integration of ScanCloud and a deep reinforcement learning method called deep deterministic policy gradient (DDPG) to adapt the operation of GPR system. The proposed method is evaluated using GPR modeling software called GprMax. Simulation results show the efficacy of ScanCloud and the adaptive GPR system enabled by the integration of ScanCluod and DDPG. 

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4. Functional connectivity uniqueness and variability? Linkages with cognitive and psychiatric problems in children

   https://doi.org/10.1038/s44220-023-00151-8  

   Fu, Zening; Liu, Jingyu; Salman, Mustafa S; Sui, Jing; Calhoun, Vince D (December 2023, Nature Mental Health)

   Abstract Brain functional connectivity (FC) derived from functional magnetic resonance imaging has been serving as a potential ‘fingerprint’ for adults. However, cross-scan variation of FC can be substantial and carries biological information, especially during childhood. Here we performed a large-scale cross-sectional analysis on cross-scan FC stability and its associations with a diverse range of health measures in children. Functional network connectivity (FNC) was extracted via a hybrid independent component analysis framework on 9,071 participants and compared across four scans. We found that FNC can identify a given child from a large group with high accuracy (maximum >94%) and replicated the results across multiple scans. We then performed a linear mixed-effects model to investigate how cross-scan FNC stability was predictive of children’s behaviour. Although we could not find strong relationships between FNC stability and children’s behaviour, we observed significant but small associations between them (maximumr = 0.1070), with higher stability correlated with better cognitive performance, longer sleep duration and less psychotic expression. Via a multivariate analysis method, we captured larger effects between FNC stability and children’s cognitive performance (maximumr = 0.2932), which further proved the relevance of FNC stability to neurocognitive development. Overall, our findings show that a child’s connectivity profile is not only intrinsic but also exhibits reliable variability across scans, regardless of brain growth and development. Cross-scan connectivity stability may serve as a valuable neuroimaging feature to draw inferences on early cognitive and psychiatric behaviours in children. 

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5. Simultaneous multislice EPI prospective motion correction by real‐time receiver phase correction and coil sensitivity map interpolation

   https://doi.org/10.1002/mrm.29789  

   Li, Bo; Li, Ningzhi; Wang, Ze; Balan, Radu; Ernst, Thomas (January 2023, Magnetic Resonance in Medicine)

   Purpose: To improve the image reconstruction for prospective motion correction (PMC) of simultaneous multislice (SMS) EPI of the brain, an update of receiver phase and resampling of coil sensitivities are proposed and evaluated. Methods: A camera-based system was used to track head motion (3 translations and 3 rotations) and dynamically update the scan position and orientation. We derived the change in receiver phase associated with a shifted field of view (FOV) and applied it in real-time to each k-space line of the EPI readout trains. Second, for the SMS reconstruction, we adapted resampled coil sensitivity profiles reflecting the movement of slices. Single-shot gradient-echo SMS-EPI scans were performed in phantoms and human subjects for validation. Results: Brain SMS-EPI scans in the presence of motion withPMCand no phase correction for scan plane shift showed noticeable artifacts. These artifacts were visually and quantitatively attenuated when corrections were enabled. Correcting misaligned coil sensitivity maps improved the temporal SNR (tSNR) of time series by 24% (p=0.0007) for scans with large movements (up to ∼35mm and 30◦). Correcting the receiver phase improved the tSNR of a scan with minimal head movement by 50% from 50 to 75 for a United Kingdom biobank protocol. Conclusion: Reconstruction-induced motion artifacts in single-shot SMS-EPI scans acquired with PMC can be removed by dynamically adjusting the receiver phase of each line across EPI readout trains and updating coil sensitivity profiles during reconstruction. The method may be a valuable tool for SMS-EPI scans in the presence of subject motion. 

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