Harmonic Approach Research Articles

Implementing verifiable oncological imaging by quality assurance and optimization (i‑Violin) : Protocol for aEuropean multicenter study.

Advanced imaging techniques play apivotal role in oncology. Alarge variety of computed tomography (CT) scanners, scan protocols, and acquisition techniques have led to awide range in image quality and radiation exposure. This study aims at implementing verifiable oncological imaging by quality assurance and optimization (i-Violin) through harmonizing image quality and radiation dose across Europe. The 2‑year multicenter implementation study outlined here will focus on CT imaging of lung, stomach, and colorectal cancer and include imaging for four radiological indications: diagnosis, radiation therapy planning, staging, and follow-up. Therefore, 480 anonymized CT data sets of patients will be collected by the associated university hospitals and uploaded to arepository. Radiologists will determine key abdominopelvic structures for image quality assessment by consensus and subsequently adapt apreviously developed lung CT tool for the objective evaluation of image quality. The quality metrics will be evaluated for their correlation with perceived image quality and the standardized optimization strategy will be disseminated across Europe. The results of the outlined study will be used to obtain European reference data, to build teaching programs for the developed tools, and to create aculture of optimization in oncological CT imaging. The study protocol and rationale for i‑Violin, aEuropean approach for standardization and harmonization of image quality and optimization of CT procedures in oncological imaging, is presented. Future results will be disseminated across all EU member states, and i‑Violin is thus expected to have asustained impact on CT imaging for cancer patients across Europe.

Superpixel-ComBat modeling: A joint approach for harmonization and characterization of inter-scanner variability in T1-weighted images

Abstract T1-weighted imaging holds wide applications in clinical and research settings; however, the challenge of inter-scanner variability arises when combining data across scanners, which impedes multi-site research. To address this, post-acquisition harmonization methods such as statistical or deep learning approaches have been proposed to unify cross-scanner images. Nevertheless, how inter-scanner variability manifests in images and derived measures, and how to harmonize it in an interpretable manner, remains underexplored. To broaden our knowledge of inter-scanner variability and leverage it to develop a new harmonization strategy, we devised a pipeline to assess the interpretable inter-scanner variability in matched T1-weighted images across four 3T MRI scanners. The pipeline incorporates ComBat modeling with 3D superpixel parcellation algorithm (namely SP-ComBat), which estimates location and scale effects to quantify the shift and spread in relative signal distributions, respectively, concerning brain tissues in the image domain. The estimated parametric maps revealed significant contrast deviations compared to the joint signal distribution across scanners (p < 0.001), and the identified deviations in signal intensities may relate to differences in the inversion time acquisition parameter. To reduce the inter-scanner variability, we implemented a harmonization strategy involving proper image preprocessing and site effect removal by ComBat-derived parameters, achieving substantial improvement in image quality and significant reduction in variation of volumetric measures of brain tissues (p < 0.001). We also applied SP-ComBat to evaluate and characterize the performance of various image harmonization techniques, demonstrating a new way to assess image harmonization. In addition, we reported various metrics of T1-weighted images to quantify the impact of inter-scanner variation, including signal-to-noise ratio, contrast-to-noise ratio, signal inhomogeneity index, and structural similarity index. This study demonstrates a pipeline that extends the implementation of statistical ComBat method to the image domain in a practical manner for characterizing and harmonizing the inter-scanner variability in T1-weighted images, providing further insight for the studies focusing on the development of image harmonization methodologies and their applications.

Harmonic analysis approach to the proof of Heisenberg inequality

the Heisenberg uncertainty Principle is a fundamental principle in quantum mechanics, which was developed by the German physicist Werner Heisenberg and was proposed by him in 1927. This principle states that for a pair of physical quantities that share phase space, such as position and momentum, it is impossible to accurately measure their values at the same time. There are several variants of it in harmonic analysis studies, and the article will introduce some of them in R^1 space and L^2 space. In the process of providing the Heisenberg inequality, the article proved the Plancherel identity and Schwartz inequality by using Fourier transform and inverse Fourier transform. Finally, author solved the equation of the wave function (x) . The famous physicists Heisenberg proposed one of the more novel ideas in quantum mechanics the existence of unobservable orbits cannot be assumed, which did bring great influence in quantum mechanics. The article will introduce the conception of Heisenberg inequality and try to finish the proof.

Harmonic analysis approach to the proof of Heisenberg inequality

the Heisenberg uncertainty Principle is a fundamental principle in quantum mechanics, which was developed by the German physicist Werner Heisenberg and was proposed by him in 1927. This principle states that for a pair of physical quantities that share phase space, such as position and momentum, it is impossible to accurately measure their values at the same time. There are several variants of it in harmonic analysis studies, and the article will introduce some of them in R^1 space and L^2 space. In the process of providing the Heisenberg inequality, the article proved the Plancherel identity and Schwartz inequality by using Fourier transform and inverse Fourier transform. Finally, author solved the equation of the wave function (x) . The famous physicists Heisenberg proposed one of the more novel ideas in quantum mechanics the existence of unobservable orbits cannot be assumed, which did bring great influence in quantum mechanics. The article will introduce the conception of Heisenberg inequality and try to finish the proof.

Off-shell invariants of linearized 4D,N=2 supergravity in the harmonic approach

Using the harmonic superspace approach, we construct, at the linearized level, N=2 supersymmetric curvatures generalizing scalar curvature, Ricci curvature and Weyl tensor. These supercurvatures are the building blocks of various linearized 4D,N=2 Einstein supergravity invariants. The supercurvatures involving the scalar and Ricci curvatures are analytic harmonic N=2 superfields, while the Weyl supertensor is a chiral N=2 superfield. As the basic distinguished feature of our construction, all these objects are expressed through the fundamental analytic gauge prepotentials h++M,M=(αα˙,α+,α˙+,5). The related characteristic features are the heavy use of harmonic derivatives and harmonic zero-curvature equations. On a number of instructive examples, we describe the component reduction of the superfield invariants constructed. Published by the American Physical Society 2024

DeepResBat: Deep residual batch harmonization accounting for covariate distribution differences

Pooling MRI data from multiple datasets requires harmonization to reduce undesired inter-site variabilities, while preserving effects of biological variables (or covariates). The popular harmonization approach ComBat uses a mixed effect regression framework that explicitly accounts for covariate distribution differences across datasets. There is also significant interest in developing harmonization approaches based on deep neural networks (DNNs), such as conditional variational autoencoder (cVAE). However, current DNN approaches do not explicitly account for covariate distribution differences across datasets. Here, we provide mathematical results, suggesting that not accounting for covariates can lead to suboptimal harmonization. We propose two DNN-based covariate-aware harmonization approaches: covariate VAE (coVAE) and DeepResBat. The coVAE approach is a natural extension of cVAE by concatenating covariates and site information with site- and covariate-invariant latent representations. DeepResBat adopts a residual framework inspired by ComBat. DeepResBat first removes the effects of covariates with nonlinear regression trees, followed by eliminating site differences with cVAE. Finally, covariate effects are added back to the harmonized residuals. Using three datasets from three continents with a total of 2787 participants and 10,085 anatomical T1 scans, we find that DeepResBat and coVAE outperformed ComBat, CovBat and cVAE in terms of removing dataset differences, while enhancing biological effects of interest. However, coVAE hallucinates spurious associations between anatomical MRI and covariates even when no association exists. Future studies proposing DNN-based harmonization approaches should be aware of this false positive pitfall. Overall, our results suggest that DeepResBat is an effective deep learning alternative to ComBat. Code for DeepResBat can be found here: https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/harmonization/An2024_DeepResBat.

Minimizing conduction losses in multiple active bridge converters across wide voltage ranges using advanced dual‐duty modulation

AbstractMultiple port DC/DC converters have applications in many fields: hybrid energy storage systems where batteries are combined with supercapacitors, multi‐level and multi‐modular inverters that need multiple DC sources, and DC microgrids. Among these converters, the Multiple Active Bridge (MAB) is particularly attractive due to its high power ratings and galvanic isolation capabilities. This paper introduces an advanced dual‐duty modulation technique for MAB converters designed to significantly reduce conduction losses over a wide range of input voltages by minimizing the harmonics’ reactive power on the AC stage. Consequently, it can improve the converter's efficiency when dealing with non‐constant voltage sources such as batteries and supercapacitors. The overall control technique is based on the dq‐frame control method under the first harmonic approach (FHA). This method is verified through simulations and implemented in a 1000 W triple‐port prototype. In the simulation, conductive and switching losses are modelled, and the trade‐off between these loss types is discussed. The experimental results affirm an overall improvement in efficiency for certain scenarios involving non‐unit voltage conversion ratios.

A reconstruction method for harmonic measurement in distribution networks based on equivalent harmonic source approach

Abstract In recent years, with a large number of nonlinear devices connected to the distribution network, harmonic problems have been inevitably generated during operation, which makes harmonic problems more complex in the distribution network. However, it is important to master the real-time harmonic level of the distribution network for the analysis and management of the harmonic problems in the grid. However, because of economic reasons and decentralized nodes, it is impractical to install a harmonic measurement device at each node in engineering. Moreover, it is important to know how to measure harmonics at important nodes in a distribution network using a limited number of measurement devices. Therefore, a harmonic measurement reconstruction method for distribution networks is proposed based on the equivalent harmonic source method. This method aims to obtain more harmonic source state information with a minimum economic cost. First, a mathematical model of the harmonic currents is established. Subsequently, an equivalent harmonic source method is proposed, and a harmonic reconstruction model based on the equivalent harmonic source method is presented. Finally, an example of an IEEE 14-node distribution network is used to verify the effectiveness of the equivalent harmonic source method.

Numerical harmonic modelling of low wattage LED lamps based on parameter estimation algorithms

This paper presents a numerical harmonic modeling approach for 18 low-wattage Light-Emitting Diode (LED) lamps. The proposed methodology utilizes meta-heuristic algorithms, namely Multi-Stage Ant Colony Optimization (MSACO) and Harris Hawk Optimization (HHO), to estimate optimal parameters for the equivalent circuits. Additionally, the study examines eight different configurations of Electromagnetic Interference (EMI) Filter circuits, including their respective parameters, which function as front-end circuits for the Full Bridge Rectifier (FBR) of the LED drivers. Through extensive investigations, the primary objective is to establish generalized and accurate models for various EMI filter circuits that can be universally applied, with validation through comparison against experimental results. Under both MSACO and HHO, the lowest average total error ranges were observed in the LC-Filter and CL-Filter configurations, with errors ranging from 21.302 % and 22.769 %, respectively. On the other hand, the L-Filter and R-only configurations exhibited the highest average total error ranges, with errors of 42.376 % and 44.648 %, respectively. Notably, this paper introduces a non-intrusive, non-invasive method for estimating optimal parameters based solely on measurements obtained from the input terminals of the LED lamps.

Charting the Course: A Policy Perspective on the Evolution of Kebbi State's Health Sector Annual Operational Planning

<i>Aim</i>: This study aims to provide a comprehensive overview of the Annual Operational Planning (AOP) process, a key health sector planning and harmonization approach, in Kebbi State, Nigeria, from 2020 to 2024, focusing on nine optimal planning parameters: state ownership, stakeholder participation, sector harmonization, evidence-based, timeliness, executive sign-off, quarterly tracking, dissemination, and sustainability. <i>Methods</i>: Review of AOP program reports, state-relevant reports, and stakeholders’ interviews. Employing a mixed-methods research design, the study integrates quantitative data derived from secondary sources like annual reports and policy documents with qualitative data from semi-structured interviews with key stakeholders. Descriptive statistics and time-series analysis are used for quantitative data to study progress and trends in each milestone, while thematic analysis of interview transcripts helps to elucidate factors influencing implementation and outcomes. <i>Results:</i> Findings highlight a progressive improvement in the annual operational planning across several of the planning parameters over the years from the baseline in 2020, including in participatory engagement of the lower levels of the health sector (bottom-up approach), using evidence to inform planning; timely development of the AOP to inform health budget; and regular tracking of the plan. However, challenges persist in the government funding of stakeholders’ engagement, particularly the bottom-up approach at the Local Government Health Authorities (LGAs) level, which may affect the inclusiveness of the process in the future. <i>Conclusion</i>: The study concludes that the annual operational planning in Kebbi State has seen notable improvement across multiple planning parameters, assuring the effectiveness and sustainability of the process as a key planning tool. However, allocating adequate resources, including budget and human resources, to facilitate a participatory approach in the AOP development process is critical for continuous success. This study contributes to the broader discourse on health sector planning in developing contexts, offering valuable insights for policymakers, health managers, and stakeholders in designing and implementing effective and harmonized health plans.

Pulsar timing array harmonic analysis and source angular correlations

Gravitational waves (GWs) influence the arrival times of radio signals coming from pulsars. Here, we investigate the harmonic space approach to describing a pulsar’s response to GWs. We derive and discuss the “diagonalized form” of the response, which is a sum of spin-2-weighted spherical harmonics of the GW direction multiplied by normal (spin-weight 0) spherical harmonics of the pulsar direction. We show how this allows many useful objects, for example, the Hellings and Downs two-point function, to be easily calculated. The approach also provides a clear description of the gauge dependence. We then employ this harmonic approach to model the effects of angular correlations in the sky locations of GW sources (sometimes called “statistical isotropy”). To do this, we construct ensembles made up of many Gaussian subensembles. While each of the individual subsensembles breaks rotational invariance, the full ensemble is rotationally invariant. Using harmonic techniques, we compute the cosmic covariance and the total covariance of the Hellings and Downs correlation in these models. The results may be used to assess the impact of angular source correlations on the Hellings and Downs correlation, and for optimal reconstruction of the Hellings and Downs curve in models where GW sources have correlated sky locations. Published by the American Physical Society 2024

Distributed Harmonization: Federated Clustered Batch Effect Adjustment and Generalization.

Independent and identically distributed (i.i.d.) data is essential to many data analysis and modeling techniques. In the medical domain, collecting data from multiple sites or institutions is a common strategy that guarantees sufficient clinical diversity, determined by the decentralized nature of medical data. However, data from various sites are easily biased by the local environment or facilities, thereby violating the i.i.d. rule. A common strategy is to harmonize the site bias while retaining important biological information. The COMBAT is among the most popular harmonization approaches and has recently been extended to handle distributed sites. However, when faced with situations involving newly joined sites in training or evaluating data from unknown/unseen sites, COMBAT lacks compatibility and requires retraining with data from all the sites. The retraining leads to significant computational and logistic overhead that is usually prohibitive. In this work, we develop a novel Cluster ComBat harmonization algorithm, which leverages cluster patterns of the data in different sites and greatly advances the usability of COMBAT harmonization. We use extensive simulation and real medical imaging data from ADNI to demonstrate the superiority of the proposed approach. Our codes are provided in https://github.com/illidanlab/distributed-cluster-harmonization.

DeepResBat: deep residual batch harmonization accounting for covariate distribution differences.

Pooling MRI data from multiple datasets requires harmonization to reduce undesired inter-site variabilities, while preserving effects of biological variables (or covariates). The popular harmonization approach ComBat uses a mixed effect regression framework that explicitly accounts for covariate distribution differences across datasets. There is also significant interest in developing harmonization approaches based on deep neural networks (DNNs), such as conditional variational autoencoder (cVAE). However, current DNN approaches do not explicitly account for covariate distribution differences across datasets. Here, we provide mathematical results, suggesting that not accounting for covariates can lead to suboptimal harmonization. We propose two DNN-based covariate-aware harmonization approaches: covariate VAE (coVAE) and DeepResBat. The coVAE approach is a natural extension of cVAE by concatenating covariates and site information with site- and covariate-invariant latent representations. DeepResBat adopts a residual framework inspired by ComBat. DeepResBat first removes the effects of covariates with nonlinear regression trees, followed by eliminating site differences with cVAE. Finally, covariate effects are added back to the harmonized residuals. Using three datasets from three continents with a total of 2787 participants and 10085 anatomical T1 scans, we find that DeepResBat and coVAE outperformed ComBat, CovBat and cVAE in terms of removing dataset differences, while enhancing biological effects of interest. However, coVAE hallucinates spurious associations between anatomical MRI and covariates even when no association exists. Future studies proposing DNN-based harmonization approaches should be aware of this false positive pitfall. Overall, our results suggest that DeepResBat is an effective deep learning alternative to ComBat. Code for DeepResBat can be found here: https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/harmonization/An2024_DeepResBat.

Comparative harmonic elimination techniques for supraharmonic reduction in microgrid

In order to reduce voltage distortion and supraharmonic (SH) emission in microgrid (MG) systems with electric vehicle (EV) charging stations, this research compares several harmonic elimination approaches. The increasing deployment of EVs has led to the integration of EV charging stations within MG systems, presents challenges in maintaining a high power quality (PQ). Voltage distortions and SH emissions are caused due to non-linear loads and the intermittent nature of EV charging, which have an effect on the performance and dependability of the MG. In order to solve these problems, multilevel converters (MLCs) are used to produce high-quality waveforms. MLCs use harmonic elimination methods to cut down on SH emissions, which improves the PQ overall. Sinusoidal pulse width modulation (PWM), selective harmonic elimination (SHE), space vector modulation (SVM), and random-PWM (RPWM) techniques are among the harmonic elimination methods compared and analyzed. The results will enable the selection of the most appropriate strategy for minimizing voltage distortion and SH emission in MG systems, while providing valuable insights into the effectiveness of each method.

Orofacial Harmonization versus Facial Deformities: A Literature Review

In the current context, orofacial harmonization can serve as a complementary means to treat deformities, whether from an aesthetic or functional perspective. In this scope, the present study aims to evaluate the use of hyaluronic acid fillers and botulinum toxin in correcting facial defects. This study consists of a literature review based on the determination of the theme, using the databases PubMed, EBSCO, SciELO, and Google Scholar. The temporal delimitation was established from 2018 to the present. The MeSH descriptors used in the research were: "hyaluronic acid filler," "facial abnormalities," and "augmentation," adding respective descriptors for each topic (ocular, nasal, ear, and lip palate oral). Data were collected between March and April 2023. A final sample of eight articles was obtained, based on the inclusion criteria adopted, with the highest number of publications identified in 2021 (n=3; 37.5%). All the results were in English, predominantly from the PubMed and Google Scholar databases. Regarding the type of facial deformity, it was observed that cleft lip and palate and chin deformity were the majority of the studies analyzed. In terms of the type of orofacial harmonization approach, hyaluronic acid injection was the most used method. Therefore, it was concluded that orofacial harmonization can assist in the rehabilitation of patients with some facial deformity, whether congenital or acquired, thus being a viable treatment option for patients with facial deformities.

Even-order optical harmonics generated from centrosymmetric-material metasurfaces

Generation of even-order optical harmonics requires noncentrosymmetric structures being conventionally observed in crystals lacking the center of inversion. In centrosymmetric systems, even-order harmonics may arise, e.g., at surfaces but such effects are usually very weak. Here we observe optical harmonics up to fourth order generated under the normal incidence from centrosymmetric dielectric metasurfaces empowered by resonances. We design silicon metasurfaces supporting optical quasibound states in the continuum and guided-mode resonances, and demonstrate the enhancement of second-harmonic signals by over three orders of magnitude compared to nonresonant thin films. Under the optimal conditions, the brightness of the second harmonic approaches that of the third harmonic, and the fourth-order harmonic becomes detectable. Published by the American Physical Society 2024

Performance of Effective Harmonic Oscillator Approach for the Calculations of Vibrational Transition Energies of Large Molecules.

The accuracy and performance of the effective harmonic oscillator approximation for the description of anharmonic vibrational structure calculations are tested for large molecular systems and compared with experimental values along with vibrational self-consistent field and second-order perturbation theories. The effective harmonic oscillator approach is an effective single-particle approximation where the variational parameters are the centroids and widths of the multidimensional Gaussian product functions posited as the vibrational wave functions. A comprehensive calculation for 849 transitions that include the fundamentals, two and three quanta overtone transitions, and several combination bands of three polyaromatic hydrocarbons and one DNA nucleobase with a total of 231 normal modes are assessed. A comparison of EHO results with the experimental values is done for the polyaromatic hydrocarbons, and a close agreement is found between the two results. It also offers anharmonic eigenstates and eigenfunctions that are nearly identical with vibrational self-consistent field theory. An extensive analysis on the resultant wave functions of the excited states is performed. The overall root-mean-square deviation (RMSD) between these two methods for 849 transitions understudy is only about 8.3 cm-1, suggesting the effective harmonic oscillator as a viable alternative for the reliable calculations of transition energies of large molecular systems.

Limits of the harmonic approach for the Morse potential

This paper presents the solution of the Morse potential via the Variational Method using a trial eigenfunction based on the harmonic oscillator and without variational parameters. The first fundamental state and the first nine excited states for the diatomic molecules of hydrogen, lithium hydride, sodium hydride, oxygen, carbon monoxide and silicon monoxide are calculated. The results obtained by the variational method are compared with the values obtained by the exact solution of the same potential in order to establish a percentage error for each energy level of the molecules analyzed and to verify up to which level the chosen trial eigenfunction describes the original system well. That shows that the approximation of the trial eigenfunction is reasonable for the first excited states. From the fourth or fifth excited state, depending on the molecule, the discrepancy no longer reasonable.

Harmonic balance applied to a 2D nonlinear finite‐element magnetic model with motion and circuit coupling

AbstractIn this work, the harmonic balance approach is applied to a 2D nonlinear finite‐element magnetic model with motion, coupled to a nonlinear circuit. The case study comprises a six‐pole three‐phase surface‐mounted permanent magnet generator connected to a six‐pulse full‐wave diode bridge rectifier. Simulations are performed at fixed generator speed in two operating cases: with an open‐circuit DC bus and supplying a load resistance. Both time stepping and harmonic balance approaches are deeply discussed focusing on the model under study, along with relevant implementation details. Harmonic balance results are compared with benchmark time stepping simulations in terms of voltage and current waveforms, progressively expanding the harmonic spectrum. The computational cost of the two approaches is reported as well. Simulation accuracy is satisfying with regard to time stepping benchmark results: relative errors on total harmonic distortion and global root‐mean‐square values are lower than 3% and 1%, respectively. However, the time stepping approach outperforms the harmonic balance one, due to the relatively short initial transient of the chosen case study. Further improvements on practical implementation are needed to exploit the potentialities of harmonic balance technique.

A new spherical harmonic approach to residual terrain modeling: a case study in the central European Alps

For decades, the residual terrain model (RTM) concept (Forsberg and Tscherning in J Geophys Res Solid Earth 86(B9):7843–7854, https://doi.org/10.1029/JB086iB09p07843, 1981) has been widely used in regional quasigeoid modeling. In the commonly used remove-compute-restore (RCR) framework, RTM provides a topographic reduction commensurate with the spectral resolution of global geopotential models. This is usually achieved by utilizing a long-wavelength (smooth) topography model known as reference topography. For computation points in valleys this neccessitates a harmonic correction (HC) which has been treated in several publications, but mainly with focus on gravity. The HC for the height anomaly only recently attracted more attention, and so far its relevance has yet to be shown also empirically in a regional case study. In this paper, the residual spherical-harmonic topographic potential (RSHTP) approach is introduced as a new technique and compared with the classic RTM. Both techniques are applied to a test region in the central European Alps including validation of the quasigeoid solutions against ground-truthing data. Hence, the practical feasibility and benefits for quasigeoid computations with the RCR technique are demonstrated. Most notably, the RSHTP avoids explicit HC in the first place, and spectral consistency of the residual topographic potential with global geopotential models is inherently achieved. Although one could conclude that thereby the problem of the HC is finally solved, there remain practical reasons for the classic RTM reduction with HC. In this regard, both intra-method comparison and ground-truthing with GNSS/leveling data confirms that the classic RTM (Forsberg and Tscherning 1981; Forsberg in A study of terrain reductions, density anomalies and geophysical inversion methods in gravity field modeling. Report 355, Department of Geodetic Sciences and Surveying, Ohio State University, Columbus, Ohio, USA, https://earthsciences.osu.edu/sites/earthsciences.osu.edu/files/report-355.pdf, 1984) provides reasonable results also for a high-resolution (degree 2160) RTM, yet neglecting the HC for the height anomaly leads to a systematic bias in deep valleys of up to 10–20 cm.