Low-pass Research Articles

Superobbing and Thinning Scales for All-sky Humidity Sounder Assimilation

Abstract Humidity sounder radiances are currently thinned to 110 km spacing prior to assimilation at ECMWF and used with no averaging applied. In this paper, the thinning scale and possible averaging of all-sky humidity sounder observations into “superobs” are considered. The short- and medium-range forecast impacts of changing the thinning and averaging scales of humidity sounder radiances prior to the data assimilation are investigated separately and then together. Superobbing acts as a low-pass filter and provides smoother images of departures, decreasing the effective sensor noise and thus the standard deviation of background departures, marginally for 183GHz channels (5-15%) and significantly for 118GHz channels (5-55%). Observations are thus more representative of the model effective resolution, with a better utilisation of total information content than thinning native-resolution radiances, as less information is discarded. Whether changed in isolation or combination, the additions of data via superobbing and finer thinning are both shown to markedly improve background fits to independent observations, indicative of better short-range forecasts of humidity and improved winds via the 4D-Var tracer effect. Wind forecasts in the Southern Hemisphere are slightly improved in the medium-range. A final configuration is tested at the resolution of the current operational model, with humidity sounder radiances averaged into 50 km superobs with 70 km spacing. This provides about 140% more radiances for assimilation and more finely detailed maps to analyse mesoscale features. The forecast impact of this change is larger in testing with higher model and data assimilation resolutions, showing the scale-dependence of such decisions and the expected performance in an operational configuration.

Recurrent neural network for predicting absence of heterozygosity from low pass WGS with ultra-low depth

BackgroundThe absence of heterozygosity (AOH) is a kind of genomic change characterized by a long contiguous region of homozygous alleles in a chromosome, which may cause human genetic disorders. However, no method of low-pass whole genome sequencing (LP-WGS) has been reported for the detection of AOH in a low-pass setting of less than onefold. We developed a method, termed CNVseq-AOH, for predicting the absence of heterozygosity using LP-WGS with ultra-low sequencing data, which overcomes the sparse nature of typical LP-WGS data by combing population-based haplotype information, adjustable sliding windows, and recurrent neural network (RNN). We tested the feasibility of CNVseq-AOH for the detection of AOH in 409 cases (11 AOH regions for model training and 863 AOH regions for validation) from the 1000 Genomes Project (1KGP). AOH detection using CNVseq-AOH was also performed on 6 clinical cases with previously ascertained AOHs by whole exome sequencing (WES).ResultsUsing SNP-based microarray results as reference (AOHs detected by CNVseq-AOH with at least a 50% overlap with the AOHs detected by chromosomal microarray analysis), 409 samples (863 AOH regions) in the 1KGP were used for concordant analysis. For 784 AOHs on autosomes and 79 AOHs on the X chromosome, CNVseq-AOH can predict AOHs with a concordant rate of 96.23% and 59.49% respectively based on the analysis of 0.1-fold LP-WGS data, which is far lower than the current standard in the field. Using 0.1-fold LP-WGS data, CNVseq-AOH revealed 5 additional AOHs (larger than 10 Mb in size) in the 409 samples. We further analyzed AOHs larger than 10 Mb, which is recommended for reporting the possibility of UPD. For the 291 AOH regions larger than 10 Mb, CNVseq-AOH can predict AOHs with a concordant rate of 99.66% with only 0.1-fold LP-WGS data. In the 6 clinical cases, CNVseq-AOH revealed all 15 known AOH regions.ConclusionsHere we reported a method for analyzing LP-WGS data to accurately identify regions of AOH, which possesses great potential to improve genetic testing of AOH.

Direct Current Motor Velocity Control With Integral Retarded Controller Under Unintentional Delay

Abstract Delay-based controllers have been recently revisited over proportional-integral-derivative (PID) controllers, with promising analytical tuning formulae and capabilities to effectively control plants with noisy measurements even without low-pass filters. One such controller is the integral retarded (IR) controller, which utilizes an intentional delay to reduce actuator chattering against noisy measurements while its integral part achieves zero steady-state error for set-point regulation of Type-0 open-loop systems. However, measurements can be unintentionally delayed in many applications. The integral retarded framework for such cases has not been studied in the literature. Here, we provide new analytical tuning rules of the controller in such cases, as well as validations through simulations and a direct current (DC) motor velocity control hardware experiment.

Integrative BNN-LHS Surrogate Modeling and Thermo-Mechanical-EM Analysis for Enhanced Characterization of High-Frequency Low-Pass Filters in COMSOL

Integrative BNN-LHS Surrogate Modeling and Thermo-Mechanical-EM Analysis for Enhanced Characterization of High-Frequency Low-Pass Filters in COMSOL

Hadamard Error-Correcting Codes and Their Application in Digital Watermarking

In communication technologies such as digital watermarking, wireless sensor networks (WSNs), and visual light communication (VLC), error-correcting codes are crucial. The Enhanced Hadamard Error-Correcting Code (EHC), which is based on 2D Hadamard Basis Images, is a novel error correction technique that is presented in this study. This technique is used to evaluate the effectiveness of the video watermarking scheme. Even with highly sophisticated embedding techniques, watermarks usually fail to resist such comprehensive attacks because of the extraordinarily high compression rate of approximately 1:200 that is frequently employed in video dissemination. It can only be used in conjunction with a sufficient error-correcting coding method. This study compares the efficacy of the well-known Reed–Solomon Code with this novel technique, the Enhanced Hadamard Error-Correcting Code (EHC), in maintaining watermarks in embedded videos. The main idea behind this newly created multidimensional Enhanced Hadamard Error-Correcting Code is to use a 1D Hadamard decoding approach on the 2D base pictures after they have been transformed into a collection of one-dimensional rows. Following that, the image is rebuilt, allowing for a more effective 2D decoding procedure. Using this technique, it is possible to exceed the theoretical error-correcting capacity threshold of ⌊dmin−12⌋ bits, where dmin is the Hamming distance. It may be possible to achieve better results by converting the 2D EHC into a 3D format. The new Enhanced Hadamard Code is used in a video watermarking coding scheme to show its viability and efficacy. The original video is broken down using a multi-level interframe wavelet transform during the video watermarking embedding process. Low-pass filtering is applied to the video stream in order to extract a certain frequency range. The watermark is subsequently incorporated using this filtered section. Either the Reed–Solomon Correcting Code or the Enhanced Hadamard Code is used to protect the watermarks. The experimental results show that EHC far outperforms the RS Code and is very resilient against severe MPEG compression.

Optimized Wide-Angle Metamaterial Edge Filters: Enhanced Performance with Multi-Layer Designs and Anti-Reflection Coatings

Optimized Wide-Angle Metamaterial Edge Filters: Enhanced Performance with Multi-Layer Designs and Anti-Reflection Coatings

Scalar radiation with a quartic Galileon

The class of Galileon scalar fields theories encapsulate the Vainshtein screening mechanism, which is characteristic of a large range of infrared modified theories of gravity. Such theories can lead to testable departures from general relativity through fifth forces and new scalar modes of gravitational radiation. However, the inherent nonlinearity of the Vainshtein mechanism has limited analytic attempts to describe Galileon theories with both cubic and quartic interactions. To improve on this, we perform direct numerical simulations of the quartic Galileon model for a rotating binary source and infer the power spectrum of given multipoles. To tame numerical instabilities we utilize a low-pass filter, extending previous work on the cubic Galileon. Our findings show that the multipole expansion is well defined and under control. Moreover, our results confirm that despite being a nonlinear scalar, the dominant Galileon radiation is quadrupole, and we find a new scaling behavior deep inside the Vainshtein region. Published by the American Physical Society 2024

Novel Illumination-invariant Face Recognition Approach via Reflectance-luminance and Local Matching Model with Weighted Voting System

In this study, a novel approach has been introduced for face recognition that is unaffected by changes in illumination. This method is based on the reflectance-luminance model and incorporates local matching using a weighted voting technique to eliminate any artifacts present in the retina images. A total of 37 different linear and nonlinear filters were tested, including high pass and low pass filters, to achieve the reflectance component of the image, which remains invariant to changes in illumination. Among these filters, the maximum filter, which is a simple filter with low computational complexity, yielded the best results in extracting the illumination invariants. It was observed that the illumination invariants obtained through this method outperformed other methods such as QI, SQI, and image enhancement techniques in terms of recognition accuracy. Importantly, the proposed method does not require any prior knowledge about the facial shape or illumination conditions and can be applied to individual images independently. Unlike many existing methods, this approach does not rely on multiple images during the training stage and does not require any parameter selection to generate the illumination invariants. To further enhance the robustness of illumination, a weighted voting system was introduced. Certain regions of the image, which may adversely affect the recognition outcome due to poor illumination, occlusion, noise, or lack of distinctive information, were identified using predefined factors such as grayscale mean, image entropy, and mutual information. The proposed method was also compared to other face recognition methods in the presence of occlusions, and it demonstrated promising results outperforming existing methods. The Python algorithm successfully detects obstructed faces, genders, and ages in videos with a face matching accuracy between 80.9% to 96.9% based on proximity.

The Parameters Governing the Anti-Myopia Efficacy of Chromatically Simulated Myopic Defocus in Tree Shrews.

We previously showed that exposing tree shrews (Tupaia belangeri, small diurnal mammals closely related to primates) to chromatically simulated myopic defocus (CSMD) counteracted small-cage myopia and instead induced hyperopia (approximately +4 diopters [D]). Here, we explored the parameters of this effect. Tree shrews were exposed to the following interventions for 11 days: (1) rearing in closed (n=7) or open (n=6) small cages; (2) exposed to a video display of Maltese cross images with CSMD combined with overhead lighting (n=4); (3) exposed to a video display of Maltese cross images with zero blue contrast ("flat blue," n=8); and (4) exposed to a video display of black and white grayscale tree images with different spatial filtering (blue pixels lowpass <1 and <2 cycles per degree [CPD]) for the CSMD. (1) Tree shrews kept in closed cages, but not open cages, developed myopia. (2) Overhead illumination reduced the hyperopia induced by CSMD. (3) Zero-blue contrast produced hyperopia but slightly less than the CSMD. (4) Both of the CSMD tree images counteracted small cage myopia, but the one low pass filtering blue <1 CPD was more effective at inducing hyperopia. Any pattern with reduced blue contrast at and below approximately 1 CPD counteracts myopia/promotes hyperopia, but maximal effectiveness may require that the video display be the brightest object in the environment. Chromatically simulated myopic blur might be a powerful anti-myopia therapy in children, but the parameter selection could be critical. Issues for translation to humans are discussed.

Microstrip Quasi-Elliptic Absorptive Bandpass Filter with Ultra-Wide Reflectionless Range and Compact Size

Absorptive bandpass filters (ABPFs) are highly attractive in modern microwave communication systems due to their ability to internally absorb the harmful stopband RF-power reflections. This paper reports an approach to designing quasi-elliptic ABPFs with ultra-wide reflectionless range, enhanced selectivity, and compact size. The method is realized based on a fourth-order quasi-elliptic absorptive lowpass filter (ALPF) prototype with a simplified structure. This ALPF prototype exhibits both good impedance-matching over the whole normalized frequency domain and an adjustable transmission zero close to the passband. By applying an equivalent impedance transformer model, a coupled-line-based ABPF scheme is devised from the ALPF prototype, which eliminates conventional dispersive transmission line inverters, resulting in an ultra-wide reflectionless range and a compact size. Closed-form equations are derived to support the filter synthesis. A 2.45 GHz microstrip ABPF with 30% fractional bandwidth is designed for verification. The measured minimum in-band insertion loss is 0.83 dB and the reflectionless range of return loss better than 10 dB is from DC to 12.88 GHz. Both the upper and lower stopband suppression exceed 20 dB, with the upper stopband extending up to 6.80 GHz. The upper and lower out-of-band roll-off rates are 93.9 and 121.4 dB/GHz, respectively. The overall circuit size is 0.12 λg2.

Optimizing control for strike point sweeping using lower divertor coil in EAST

In 2021, EAST was equipped with a full-ring divertor coil to facilitate research on the fish tail divertor concept. Initially, it was observed that the coil current had a negligible ability to sweep the strike point. Conversely, when the amplitude and frequency of the alternating current were marginally increased, there was a significant interruption to plasma control. This perturbation was attributed to the poloidal control field’s limited response rate to the coil’s fluctuations. To address this issue, novel control methodologies were devised to ensure stable and effective sweeping of the strike point using the divertor coil. The devised methods are twofold: For high-frequency strike point control, a low-pass filter decoupling technique based on ISOFLUX control strategy enabled achieving a sweeping frequency of 100 Hz. This strategy allowed for consistent plasma management without compromising average stored energy or density regulation. Resulting from this proficient manipulation of the strike point, a reduction in the peak temperature of the divertor plate was observed. For low-frequency sweeping, a static multi-input multi-output decoupling approach was developed, facilitating concurrent sweeping of both the outer and inner strike points.

An improvement in block matching algorithms using a dissimilarity measure in frequency domain transform

In this work, the image block matching based on dissimilarity measure is investigated. Moreover, an unsupervised approach is implemented to yield that the algorithms have low complexity (in numbers of operations) compared to the full search algorithm. The state-of-the-art experiments only use discrete cosine transform as a domain transform. In addition, some images were tested to evaluate the algorithms. However, these images were not evaluated according to specific characteristics. So, in this paper, an improved version is presented to tackle the problem of dissimilarity measure in block matching with a noisy environment, using another’s domain transforms or low-pass filters to obtain a better result in block matching implementing a quantitive measure with an average accuracy margin of ± 0.05 is obtained. The theoretical analysis indicates that the complexity of these algorithms is still accurate, so implementing Hadamard spectral coefficients and Fourier filters can easily be adjusted to obtain a better accuracy of the matched block group.

A connecting rod assembly deformation cognition method based on quality characteristics probability network

As the core component of marine diesel engines, the connecting rod quality directly affects the reliability and life of diesel engines. However, the deformation problem of the connecting rod assembly process, which caused the low pass rate of one-time assembly, has not been well solved. The deformation of connecting rod assembly is difficult to analyze by mechanism because it is influenced by many quality characteristics with complex and cross-process correlations. To address this issue, this paper proposes a connecting rod assembly deformation cognition method based on the quality characteristics probability network. Firstly, a quality characteristics probabilistic network model for the connecting rod assembly process is established. Secondly, based on the quality characteristics probability network model and the complexity of cross-process correlation, the K-shell entropy weight model is used to identify the key quality characteristics and construct their correlation model. Then, to deal with the uncertainty of the influence degree between quality characteristics, a Bayesian network is used to establish an influence analysis model of key quality characteristics and analyze their influence relationship from qualitative and quantitative perspectives. Finally, the simulation and actual assembly data of marine diesel engine connecting rod assembly process are used to train and verify the cognition method. The results show that the method can effectively analyze the relationship between the connecting rod assembly process quality characteristics and predict the connecting rod deformation degree. The proposed method can comprehensively consider the influence of multiple processes and quality characteristics, improve the accuracy of analysis and prediction of connecting rod deformation, and can be used to guide the dynamic adjustment of the connecting rod assembly process to increase the pass rate of one-time. Moreover, the proposed method can also provide a reference for other multi-process and multi-factor problem analyses.

GaN low noise amplifier MMIC with LPF and HPF noise matching

In this paper, we introduce two innovative two-stage low noise amplifiers (LNAs), each with distinct noise-matching networks. The first LNA features a low pass filter (LPF) for noise-matching in both stages, while the second uses a high pass filter (HPF) in a similar capacity. Our research focuses on evaluating the performance differences that arise from using varied matching networks within specific frequency ranges. Highlighting the critical role of appropriate network selection for optimizing gain and noise performance, our approach includes the development of two Monolithic Microwave Integrated Circuits (MMICs) using cutting-edge 0.25μm Gallium Nitride (GaN) technology. The C-band LNA, targeting a frequency range of 4–6 GHz, achieves an impressive average noise fig. (NF) of 1.5 dB and a gain of 17 dB. For the X-band range of 8–10 GHz, the LNA records a commendable average NF of 1.7 dB and a gain of 16 dB, demonstrating the effectiveness of our novel design strategies.

Commissioning of a novel PET-Linac for biology-guided radiotherapy (BgRT).

Biology-guided radiotherapy (BgRT) is a novel radiotherapy delivery technique that utilizes the tumor itself to guide dynamic delivery of treatment dose to the tumor. The RefleXion X1 system is the first radiotherapy system developed to deliver SCINTIX® BgRT. The X1 is characterized by its split arc design, employing two 90-degree positron emission tomography (PET) arcs to guide therapeutic radiation beams in real time, currently cleared by FDA to treat bone and lung tumors. This study aims to comprehensively evaluate the capabilities of the SCINTIX radiotherapy delivery system by evaluating its sensitivity to changes in PET contrast, its adaptability in the context of patient motion, and its performance across a spectrum of prescription doses. A series of experimental scenarios, both static and dynamic, were designed to assess the SCINTIX BgRT system's performance, including an end-to-end test. These experiments involved a range of factors, including changes in PET contrast, motion, and prescription doses. Measurements were performed using a custom-made ArcCHECK insert which included a 2.2cm spherical target and a c-shape structure that can be filled with a PET tracer with varying concentrations. Sinusoidal and cosine4 motion patterns, simulating patient breathing, was used to test the SCINTIX system's ability to deliver BgRT during motion-induced challenges. Each experiment was evaluated against specific metrics, including Activity Concentration (AC), Normalized Target Signal (NTS), and Biology Tracking Zone (BTZ) bounded dose-volume histogram (bDVH) pass rates. The accuracy of the delivered BgRT doses on ArcCHECK and EBT-XD film were evaluated using gamma 3%/2mm and 3%/3mm analysis. In static scenarios, the X1 system consistently demonstrated precision and robustness in SCINTIX dose delivery. The end-to-end delivery to the spherical target yielded good results, with AC and NTS values surpassing the critical thresholds of 5 kBq/mL and 2, respectively. Furthermore, bDVH analysis consistently confirmed 100% pass rates. These results were reaffirmed in scenarios involving changes in PET contrast, emphasizing the system's ability to adapt to varying PET avidities. Gamma analysis with 3%/2mm (10% dose threshold) criteria consistently achieved pass rates>91.5% for the static tests. In dynamic SCINTIX delivery scenarios, the X1 system exhibited adaptability under conditions of motion. Sinusoidal and cosine4 motion patterns resulted in 3%/3mm gamma pass rates>87%. Moreover, the comparison with gated stereotactic body radiotherapy (SBRT) delivery on a conventional c-arm Linac resulted in 93.9% gamma pass rates and used as comparison to evaluate the interplay effect. The 1cm step shift tests showed low overall gamma pass rates of 60.3% in ArcCHECK measurements, while the doses in the PTV agreed with the plan with 99.9% for 3%/3mm measured with film. The comprehensive evaluation of the X1 radiotherapy delivery system for SCINTIX BgRT demonstrated good agreement for the static tests. The system consistently achieved critical metrics and delivered the BgRT doses per plan. The motion tests demonstrated its ability to co-localize the dose where the PET signal is and deliver acceptable BgRT dose distributions.

Ultrabright Dibenzofluoran-Based Polymer Dots with NIR-IIa Emission Maxima and Unusual Large Stokes Shifts for 3D Rotational Stereo Imaging.

Emerging organic molecules with emissions in the second near-infrared (NIR-II) region are garnering significant attention. Unfortunately, achieving accountable organic emission intensity over the NIR-IIa (1300nm) region faces challenges due to the intrinsic energy gap law. Up to the current stage, all reported organic NIR-IIa emitters belong to polymethine-based dyes with small Stokes shifts (<50nm) and low quantum yield (QY; ≤0.015%). However, such polymethines have proved to cause self-absorption with constrained emission brightness, limiting advanced development in deep-tissue imaging. Here a new NIR-IIa scaffold based on rigid and highly conjugated dibenzofluoran core terminated by amino-containing moieties that reveal emission peaks of 1230-1305nm is designed. The QY is at least 10 times higher than all synthesized or reported NIR-IIa polymethines with extraordinarily large Stokes shifts of 370-446nm. DBF-BJ is further prepared as a polymer dot to demonstrate its in vivo 3D stereo imaging of mouse vasculature with a 1400nm long-pass filter.

NP-MBO: A newton predictor-based momentum observer for interaction force estimation of legged robots

Swift perception of interaction forces is a crucial skill required for legged robots to ensure safe human–robot interaction and dynamic contact management. Proprioceptive-based interactive force is widely applied due to its outstanding cross-platform versatility. In this paper, we present a novel interactive force observer, which possesses superior dynamic tracking performance. We propose a dynamic cutoff frequency configuration method to replace the conventional fixed cutoff frequency setting in the traditional momentum-based observer (MBO). This method achieves a balance between rapid tracking and noise suppression. Moreover, to mitigate the phase lag introduced by the low-pass filtering, we cascaded a Newton Predictor (NP) after MBO, which features simple computation and adaptability. The precision analysis of this method has been presented. We conducted extensive experiments on the point-foot biped robot BRAVER to validate the performance of the proposed algorithm in both simulation and physical prototype.

Abstract PS06-07: Liquid biopsy determination of HER2 status in breast cancer: results from a novel epigenomic platform

Abstract Background: Tumor HER2 status remains a critical predictive biomarker for patients with breast cancer given the availability of highly effective anti-HER2 therapies. However, determination of HER2 status relies on a complex, tissue-dependent algorithm optimized for extremes of the phenotype – HER2+ vs HER2- status. Given the challenges in reliably obtaining informative tissue biopsies as disease progresses, the new therapeutic relevance of HER2-low breast cancer (IHC 1+ and FISH-negative IHC 2+), and the undependability of biomarkers in this range, better approaches are needed. Epigenomic signatures detectable in cell-free tumor DNA (cfDNA) may provide a minimally invasive, reliable determination of HER2 status. Here, we present a multimodal epigenomic liquid biopsy platform that could offer a minimally invasive alternative to tissue-based determination of transcriptionally regulated targets such as HER2. Methods: We identified patients with metastatic breast cancer (n=20) that were HER2-positive with IHC 3+ (n=6) or HER2-negative with IHC 0 (n=14) based on ASCO/CAP guidelines who underwent research biopsies at the Dana-Farber Cancer Institute from 2012-2023. Study participants had undergone concurrent blood sampling collected in Streck Tubes, processed as plasma, and stored at -80ºC. We applied a novel, multimodal epigenomic assay to profile tumor-derived gene regulatory programs from 1mL plasma. This genome-wide approach analyzed histone modifications associated with active gene promoters and enhancers, and DNA methylation. Classifier feature selection was derived from epigenomically profiled breast cancer cell lines. Final classifier performance was cross validated using a standard Leave one Out (LoO) scheme. Results: Our cross-validated classifier yielded an area under the ROC curve (AUC) of 0.91 in the 20 samples tested. When including only samples with detectable ctDNA as assessed by low pass whole genome sequencing (ichorCNA algorithm) (N=13), our classifier had an AUC of 0.98. Using regularized regression approach, we identified 33 loci with the highest predictive value; 8 loci were within the ERBB2 amplicon on chromosome 17, while the remaining 25 loci were in other genomic regions. We will present results from this and an expanded cohort, including participants with HER2 IHC 1+ and 2+ disease. Conclusions: We present a novel, minimally invasive HER2 classifier leveraging epigenomic information from cell-free tumor DNA from 1 mL plasma. If this approach remains robust in accurately classifying additional HER2 states, it could address the limitations of current tissue-based testing. Integration of this epigenomic platform in prospective interventional studies could support the development of novel and improved predictive classifiers for response to HER2-directed therapy. Citation Format: Heather Parsons, Sylvan Baca, Anthony D'Ippolito, Hyun-Hwan Jeong, Kalie Smith, Paolo Tarantino, Melissa Hughes, Kerry Sendrick, Corrie Painter, Ji-Heui Seo, Elizabeth Grant, Jamey Guess, Matthew Davidsohn, Gitanjali Lakshminarayanan, Sarah Strauss, Hunter Savignano, John Canniff, Brad Fortunato, Matthew Eaton, Toni Choueiri, Sara Tolaney, Matthew Freedman, Nancy Lin. Liquid biopsy determination of HER2 status in breast cancer: results from a novel epigenomic platform [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS06-07.

Improved filtering methods to suppress cardiovascular contamination in electrical impedance tomography recordings.

Electrical Impedance Tomography (EIT) produces clinical useful visualization of the distribution of ventilation inside the lungs. The accuracy of EIT-derived parameters can be compromised by the cardiovascular signal. Removal of these artefacts is challenging due to spectral overlapping of the ventilatory and cardiovascular signal components and their time-varying frequencies. We designed and evaluated advanced filtering techniques and hypothesized that these would outperform traditional low-pass filters. &#xD;Approach: Three filter techniques were developed and compared against traditional low-pass filtering: multiple digital notch filtering (MDN), empirical mode decomposition (EMD) and the maximal overlap discrete wavelet transform (MODWT). The performance of the filtering techniques was evaluated 1) in the time domain 2) in the frequency domain 3) by visual inspection. We evaluated the performance using simulated contaminated EIT data and data from fifteen adult and neonatal ICU patients. &#xD;Main result: Each filter technique exhibited varying degrees of effectiveness and limitations. Quality measures in the time domain showed the best performance for MDN filtering. The signal to noise ratio was best for DLP, but at the cost of a high relative and removal error. MDN outbalanced the performance resulting in a good SNR with a low relative and removal error. MDN, EMD and MODWT performed similar in the frequency domain and were successful in removing the high frequency components of the data. &#xD;Significance: Advanced filtering techniques have benefits compared to traditional filters but are not always better. MDN filtering outperformed EMD and MODWT regarding quality measures in the time domain. This study emphasizes the need for careful consideration when choosing a filtering approach, depending on the dataset and the clinical/research question. &#xD.

A Robust Model Order Reduction Scheme for Lithium-Ion Batteries in Control-Oriented Vehicle Models

The role of batteries in electrification of vehicles is eminent; thus, a dynamic model that represents the physics-based phenomena of the battery system at a minimum computational cost is essential in the model-based design of electrified vehicle control systems. Furthermore, robustness of the reduced-order battery model when maintaining the dominant physics-based phenomena governing the dynamic behavior of the battery system is crucial. Characterization of the power signal applied to the lithium-ion battery in the energy management controller of a plug-in hybrid electric vehicle shows that there is a dominant frequency range in the input signal to the battery. This key feature can be considered as a basis to construct a reduced-order model in which the training input is different from the original power signal. The original idea in this paper is to generate the training input by applying a low-pass filter to the white-noise random signal to maintain the same dominant frequency range observed in the original power signal. Response of the reduced-order model, constructed using the proper orthogonal decomposition, compared to the high-fidelity battery model shows promising results; a maximum relative error of 1% was obtained for the battery state of charge while simulation time was reduced by 42.9%.