Inverse Method Research Articles

Chemical profile and biotechnological potential larvicidal of a nanoemulsion (o/w) of the essential oil of Salvia officinalis L

This study aims to evaluate the chemical profile and biotechnological larvicidal potential of the nanoemulsion of the essential oil of Salvia officinalis L. The leaves of the plant were collected in São Luís, MA, from January to May 2021. The essential oil was extracted by hydrodistillation at 100°C for 3h. Chemical characterization was obtained by GC-MS. The oil-in-water nanoemulsion was formulated by the low-energy phase inversion method and subjected to thermodynamic stability tests. Antioxidant activity is performed by the spectrophotometric method of scavenging hydroxyl radicals from salicylic acid. For larvicidal activity, Aedes aegypti larvae were subjected to EO solutions and nanoemulsions in concentrations (10-100 mg L-1), larval mortality was evaluated, and the LC50 was determined by the Probit method. The majority compounds of the EO were: eucalyptol with 65.14%, camphor (30.63%), and α-Terpineol (1.53%). The formulations were characterized as nanoemulsions with a droplet size <200 nm. The PDI was <0.200, indicating a narrow size distribution. The antioxidant activity exhibited EC50 of 136.29 mg L-1 and 51.59 mg L-1. The nanoemulsion with larvicidal potential showed an LC50 of 71.17 mg L-1. The nanoemulsion showed bioactive potential for larvicidal action, which may be related to the presence of its chemical compounds, and its use is encouraged in the fight against Aedes aegypti.

Colchicine in Patients With Coronary Disease Who Underwent Coronary Artery Bypass Surgery: A Meta-Analysis of Randomized Controlled Trials

Recent randomized evidence has shown that low-dose colchicine lowers the risk of cardiovascular events in patients with chronic coronary artery disease. Colchicine has also been used in coronary artery bypass grafting (CABG), with individual studies suggesting protective effects for postoperative atrial fibrillation (POAF). We performed a meta-analysis of studies assessing the effect of colchicine on outcomes in CABG surgery. We systematically searched 3 libraries (MEDLINE, Web of Science, and the Cochrane Library), selecting all randomized control trials including patients who underwent CABG and were randomized for perioperative administration of colchicine versus standard of care. The primary outcome was incidence of POAF. The inverse variance method (DerSimonian&Laird) and random-effects model were performed. The leave-one-out analysis was carried out as a sensitivity analysis to address possible outliers. From 205 screened studies, 5 met the inclusion criteria and were selected. The data from 839 patients were included in the final analysis. The included studies were published between 2014 and 2022. The perioperative administration of colchicine was associated with the reduction of POAF rates after CABG compared with standard of care (relative risk 0.54, 95% confidence interval 0.40 to 0.73, p <0.01). The leave-one-out analysis confirmed the robustness of the analysis, with minimal variations of the confidence interval. This meta-analysis of randomized studies suggests that the perioperative administration of colchicine is associated with significant reduction of POAF after CABG.

LoopNet for fine-grained fashion attributes editing

Generative Adversarial Networks (GANs) have revolutionized the field of image synthesis by transforming randomly sampled latent codes into high-fidelity synthesized images. However, current methods fall short in manipulating a wide range of fashion attributes due to semantic ambiguity and lack of disentanglement. This work focuses on fashion attribute editing by proposing an encoder-based GAN inversion method, namely LoopNet. To enable high-fidelity image inversion and fine-grained attribute editing, it refines edited images through two encoder–decoder stages, utilizing predefined directions from principal component analysis on latent codes and canny loss for detail enhancement. Experiments show LoopNet’s effectiveness in attribute disentanglement and manipulation, outperforming seven state-of-the-art image inversion methods.

Impact of thick N-polar AlN growth on crystalline quality and electrical properties of N-polar GaN/AlGaN/AlN FET

In this study, we attempted to fabricate N-polar GaN/AlGaN/AlN heterostructure FET by changing the thickness of the AlN layer. An Al-polar tiny-pit AlN layer and a polarity inversion method were used to grow N-polar AlN on vicinal sapphire via the metal-organic vapor phase epitaxy. The samples with an AlN thickness of up to 3.4 μm exhibited a crack-free surface. Additionally, the twist component of the crystal quality improved with an increasing AlN thickness. Consequently, the mobility, sheet conductivity, and surface flatness improved. The FET fabricated from the sample with a thicker AlN layer achieved a higher drain current of 279 mA mm−1 at a gate bias of V G = 3 V.

Light-curve analysis and shape models of NEAs 7335, 7822, 154244, and 159402

ABSTRACT In an attempt to further characterize the near-Earth asteroid (NEA) population, we present 38 new light curves acquired between 2020 September and 2023 November for NEAs (7335) 1989 JA, (7822) 1991 CS, (154244) 2002 KL6, and (159402) 1999 AP10, obtained from observations taken at the Teide Observatory (Tenerife, Spain). With these new observations along with archival data, we computed their first shape models and spin solutions by applying the light-curve inversion method. The obtained rotation periods are in good agreement with those reported in previous works, with improved uncertainties. Additionally, besides the constant period models for (7335) 1989 JA, (7822) 1991 CS, and (159402) 1999 AP10, our results for (154244) 2002 KL6 suggest that it could be affected by a Yarkovsky–O’Keefe–Radzievskii–Paddack acceleration with a value of $\upsilon \simeq -7\times 10^{-9}$ rad d$^{-2}$. This would be one of the first detections of this effect slowing down an asteroid.

Envelope normalized reflection waveform inversion

AbstractThe reflection waveform inversion has the capability to reconstruct the background velocity model using only the reflection data by employing a migration/demigration process. Utilizing the waveform discrepancy to update the background velocity model, the conventional reflection waveform inversion method heavily relies on the true‐amplitude migration/demigration technique to reproduce the primary amplitude information from the observed reflections. We can reproduce the amplitude of observed reflections by performing least‐squares reverse time migration to estimate the reflectivity in each iteration. However, this strategy is quite time‐consuming. To avoid the need for the true‐amplitude migration/demigration or least‐squares reverse time migration, we develop an amplitude‐independent reflection waveform inversion method that uses an envelope‐normalized objective function. The envelope‐normalized waveform difference can extract the phase residuals accurately as a function of time. Compared with the global energy–normalized misfit, our proposed envelope‐normalized objective function is essentially a phase‐matched measurement. At the same time, due to the amplitude independence of our proposed objective function, the subsequent weak reflections contribute with a similar weight to the total value of the misfit as the strong early reflections do. This makes it possible to recover the deep subsurface velocity. Synthetic data of the Sigsbee model and marine streamer field data applications validate that our amplitude‐independent reflection waveform inversion method can further improve the resolution and accuracy by aligning the reflection events of synthetic and observed data phase to phase without the need to perform true‐amplitude migration/demigration or least‐squares reverse time migration as in conventional reflection waveform inversion.

Investigating amplitude amplification in optimization-based control for a continuous stirred tank reactor

Quantum computers, which utilize quantum states called ‘qubits’ to process information, are becoming of increased interest in a variety of fields because they have the potential to outperform classical computers in certain situations. However, many challenges and hurdles remain, including the development of quantum algorithms that offer a speedup and can be applied to practical problems (some quantum algorithms that offer a speedup may only be applicable in specific and sometimes contrived circumstances). Our previous works have studied the use of quantum computers and quantum algorithms for process control applications. Our prior work evaluated the use of a gate-based quantum amplitude amplification algorithm when applied to a model predictive control optimization problem, specifically evaluating a linear systems example. The results suggested that the algorithm may be suited for the specific linear problem studied (meaning that there is a high probability of obtaining the desired result when measuring the quantum state after the algorithm has been applied). However, the results cannot be generalized to a wider class of systems or to systems containing nonlinearities. To begin to gain an understanding of how the amplitude amplification algorithm might be generalized, this work evaluates the use of the algorithm for the optimization-based control of a nonlinear dynamic system (specifically, a continuous stirred tank reactor). We seek to understand aspects of the problem, such as the development of a solution space, the effects of changing process and control parameters, and the operation of the amplitude amplification algorithm itself. The results demonstrate the challenges that still exist, and demonstrate a method involving inverse sampling transformations to potentially aid in addressing these issues.

Forward and inverse river contaminant transport modeling using group preserving scheme

Environmental concerns have necessitated the development of computational models predicting pollutant dispersion in natural water systems. Due to the ill-posed nature of the inverse contaminant transport equation, solving this equation using all stable and convergent inverse methods is impossible. Factors such as river geometry, unsteady and non-uniform flow, and tidal influences add to the complexity of the inverse problem. These factors have prompted the evaluation of Group Preserving Scheme for environmental applications. The inverse solution method derives a general equation for solving ordinary differential equations by addressing a dynamical system at negative time steps, ensuring convergence. Three test cases have been presented to evaluate Backward Group Preserving Scheme (BGPS). These have included validation using observational data from Missouri River, inverse simulation in a tidal river, and sensitivity analysis of parameters such as pollutant patterns, advection, dispersion, and decay coefficients. The dataset includes calibrated data from Missouri River, which demonstrated high accuracy, with Mean Relative Error (MRE) ranging from 2.8% to 5.0% for the inverse model. Under tidal conditions, accuracy decreases over time but remains robust, with a Nash–Sutcliffe efficiency of 0.77–0.96 and an MRE of 0.9%–5.9%. Sensitivity analysis revealed optimal model performance for Péclet numbers greater than 500. The model performed best with gradual, wide-peaked pollutant patterns and moderate decay rates (Damköhler number between 5 and 10). BGPS proves effective for transport simulation and concentration history reconstruction in complex rivers, including those with tidal influences, offering a robust tool for water contamination analysis in various flow conditions.

The numerical reconstruction methods for characterizing defects by full matrix data using an ultrasonic array

Abstract This study introduces ultrasonic imaging and inversion methods for the quantitative characterization of crack defects. The Total Focusing Method (TFM) is a high-precision ultrasonic imaging method, but it may produce length errors when used for large-angle defect detection. An SV transverse wave TFM method is introduced, significantly reducing length errors in a 60° crack to 8.31%. However, the ultrasonic image method is influenced by factors like array position, limiting its practicality. To overcome this limitation, the study proposes an inversion method using the subarray scattering coefficient matrix, which is more stable and less sensitive to array positioning. Comparative analysis with finite element simulations and experiments indicates optimal array positions associated with different methods. At these positions, both methods yield angular characterization errors for the 60° crack of less than 1%, validating the proposed techniques for non-destructive testing applications.

Truncated Newton full waveform inversion method for the human brain imaging

Abstract It has been shown that full-waveform inversion (FWI) method can be a competitive alternative for medical imaging problems. It offers high-resolution results while delivering the advantages of being fast, safe, portable, and affordable, compared to magnetic resonance imaging (MRI) and x-ray computed tomography. However, to the best of our knowledge, FWI applications in medical imaging only use the first-order derivative information. In this case, the high parameter contrasts between different tissues of human body and multi-scatterings problems may lead FWI to local minima. Thus, we present a competitive truncated Newton method for high-resolution imaging of the human brain. This truncated Newton method, based on the efficient linear solver MINRES-QLP, can make full use of multiple scattering wavefield information. Compared with the truncated Newton method based on conjugate gradient, the MINRES-QLP iterative method presents various advantages when solving linear systems, such as the capacity to handle both non-singular and singular systems, less computational cost, and efficiency even for ill-conditioned systems. Numerical experiments for imaging the brain with and without the skull are conducted. Numerical results indicate that, compared with the truncated Newton method based on conjugate gradient, the truncated Newton method based on MINRES-QLP exhibits computational efficiency while maintaining the same level of accuracy.

Laser ultrasonic characterization of grains in titanium alloy by the inversion method

Abstract The polycrystalline materials have been usually described by the average grain size (AGS). This paper provides a nondestructive method for determination of the AGS in titanium alloy from an inversion of experimental ultrasonic attenuation spectrum (UAS). The detailed analyses of the inverse algorithm and sensitivity of UAS to the AGS are presented, and the sensitivity is identified as a criterion for selecting the experimental data of UAS used in inversion. An example of the inverse method and experimental measurement for UAS comparison was given for the titanium alloy specimen with the AGS of 26 μm. The relative error between the AGS determined by the inversion and scanning electron microscope (SEM) observation was found to be about 1.5 %. The provided method demonstrates the feasibility of laser ultrasonic technology used for the non-destructive evaluation of AGS in polycrystalline materials.

Introducing the DI and PFSDI Methods: New Inversion Methods that Do Not Need the Low Frequency Model (LFM)

Introducing the DI and PFSDI Methods: New Inversion Methods that Do Not Need the Low Frequency Model (LFM)

Reinsurance contracts under Stackelberg game and market equilibrium

In this paper, we investigate the robust reinsurance contracts under Stackelberg game and market equilibrium. Each reinsurance contract contains two decision makers, one insurer and one reinsurer. The insurer is ambiguity-neutral and adopts a loss-dependent premium principle to collect premium. The reinsurer is ambiguity-averse and is a Bayesian learner. By using the stochastic dynamic programming method and the inverse method, the analytical expressions of the optimal risk allocation proportion and reinsurance price are derived for the two types of reinsurance contracts. We shows that the loss-dependent premium principle has the penalty-reward nature. Both the reinsurance price and demand decrease as the extrapolative intensity increases. Learning has important significance and always puts down the reinsurance price and puts up the reinsurance demand. On the contrary, the reinsurer’s ambiguity aversion raises the reinsurance price and decreases the reinsurance demand. Finally, numerical analysis reveals that the reinsurance price is greater under the Stackelberg game than that under the market equilibrium.

A novel class of non-Gaussian system performance assessment and controller parameter tuning methods

Traditional variance-based control performance assessment (CPA) and controller parameter tuning (CPT) methods tend to ignore non-Gaussian external disturbances. To address this limitation, this study proposes a novel class of CPA and CPT methods for non-Gaussian single-input single-output systems, denoted as data Gaussianization (inverse) transformation methods. The idea of quantile transformation is used to transform the non-Gaussian data with the goal of maximizing mutual information into virtual Gaussian data. In addition, optimal system data for the virtual loop are mapped back to the actual non-Gaussian system using quantile inverse transformation. Furthermore, a CARMA model-based recursive extended least square algorithm and a CARMA model-based least absolute deviation iterative algorithm are used to identify virtual Gaussian and non-Gaussian system process models, respectively, while implementing the CPT. Finally, a unified framework is proposed for the CPA and CPT of a non-Gaussian control system. The simulation results demonstrate that the proposed strategy can provide a consistent benchmark judgment criterion (threshold) for different non-Gaussian noises, and the tuned controller parameters have good performance.

Causality between autoimmune diseases and breast cancer: a two-sample Mendelian randomization study in a European population

BackgroundThe incidence of autoimmune diseases and breast cancer is significantly higher in women compared to men. Previous observational studies have not conclusively determined the relationship between these two conditions. This study utilizes the Mendelian randomization approach to investigate the genetic association between autoimmune diseases and breast cancer.MethodTwo-sample Mendelian randomization was conducted on a European population using the GWAS database. The inverse variance-weighted method served as the primary analytical approach. The MR-PRESSO test was applied to detect horizontal pleiotropy. To ensure result robustness, the FDR correction method was used.ResultThe study revealed that Sjögren’s syndrome lowers the overall risk of breast cancer (OR 0.96, 95% CI [0.93–0.99], p = 0.011). Idiopathic inflammatory myopathy shows a protective effect against overall breast cancer (OR 0.98, 95% CI [0.97–0.99], p = 0.035). An association was identified between rheumatoid arthritis and overall breast cancer (OR 0.98, 95% CI [0.96–1.00], p = 0.050). No causal link was found between systemic lupus erythematosus, systemic sclerosis, and overall breast cancer. The study also suggests that Sjögren’s syndrome, rheumatoid arthritis, and idiopathic inflammatory myopathy might reduce the risk of developing HER + breast cancer. Specifically, Sjögren’s syndrome (OR = 0.90, 95% CI [0.83–0.98], p = 0.02), rheumatoid arthritis (OR = 0.94, 95% CI [0.91–0.98], p = 0.006), and idiopathic inflammatory myopathy (OR = 0.96, 95% CI [0.93–0.99], p = 0.036). Additionally, systemic lupus erythematosus was found to lower the risk of HER- breast cancer (OR = 0.95, 95% CI [0.91–0.99], p = 0.046). The study did not establish a causal relationship between these five autoimmune diseases and ER + or ER- breast cancer.ConclusionThis study found that autoimmune diseases may act as protective factors against breast cancer risk.

Comparing Two Methods for Testing the Efficiency of Sports Betting Markets

Sports betting markets can be considered strongly efficient if expected returns on all possible bets on an event are equal. If this form of efficiency holds, then there is a direct mapping from betting odds into probabilities of outcomes of sporting events. We compare two regression-based methods for testing this form of efficiency that have been used in previous research: One that uses normalized probabilities as the explanatory variable for event outcomes and one that uses the inverse of the decimal odds. We show that the normalized probability method produces good tests of the null hypothesis of strong market efficiency but that the inverse odds method does not, with results biased against finding favorite-longshot bias. We illustrate this finding using large datasets of bets and outcomes for tennis and soccer and also with realistic simulations.

Abstract MP08: Long-Term Impact of Bariatric Surgery on Hypertension Control and Remission: A Meta-Analysis of Randomized Controlled Trials

Background: Bariatric surgery is widely recognized as a highly effective intervention for addressing obesity and its associated metabolic complications. However, there is a paucity of evidence from randomized controlled trials (RCTs) with primary endpoints focusing on its impact on hypertension. Objective: We aimed to synthesize findings from pivotal RCTs until May 2024 to evaluate the long-term effects of bariatric surgery on hypertension in obese individuals compared to medical or lifestyle management. Methods: We analyzed data using RevMan 5.4 with a random effects model, employing the inverse variance method to report outcomes as risk ratios (RR) or weighted mean differences (WMD) with 95% confidence intervals (CI). Our study protocol is registered in PROSPERO (CRD42024527369). Results: The study comprised 18 RCTs involving 1386 obese patients (62.7% women) with a mean BMI of 38 kg/m 2 and an average follow-up duration of 1 to 5 years. On pooled analysis, there was a statistically significant difference in the rate of hypertension remission between patients who underwent bariatric surgery versus patients on medical/lifestyle management with an RR of 2.77 (95% CI: 1.26 to 6.10, p = 0.01). Additionally, a substantial reduction in the use of antihypertensive medications while maintaining controlled blood pressure was observed (RR: 7.10; 95% CI: 4.38 to 11.51, p &lt; 0.00001), with no heterogeneity. Bariatric surgery also significantly improved systolic blood pressure control (WMD: -3.67; 95% CI: -5.53 to -1.80, p = 0.0001). Conclusion: Bariatric surgery emerges as a durable solution for obesity-related hypertension, offering remission and control of hypertension while reducing the dependence on antihypertensive medications.

Protein folding, protein dynamics and the topology of self-motions.

It has long been recognized that segments of the protein main chain are like robotic manipulators and inverse kinematics methods from robotics have been applied to model loops to bridge gaps in protein comparative modelling. The complex internal motion of a redundant manipulator with fixed ends is called a self-motion and its character is determined by the relative position of its ends. Self-motions that are topologically equivalent (homotopic) occupy the same continous region of the configuration space. Topologically inequivalent (non-homotopic) regions are separated by co-regular surfaces and crossing a co-regular surface can result in a sudden dramatic change in the character of the self-motion. It is shown, using a five-residue type I β-turn, that these concepts apply to protein segments and that as the ends of the five-residue segment come closer together, a co-regular surface is crossed, and the structure is locked in to becoming either a type I or type I' turn. It is also shown that the type II turn is topologically equivalent to the type I' turn, not the type I turn. These results have implications for both native-state protein dynamics and protein folding.

Bond Strength Evaluation of Ceramic Restorations with Immediate Dentin Sealing: A Systematic Review and Meta-Analysis.

Immediate dentin sealing (IDS) was introduced to overcome the disadvantages of delayed dentin sealing like pollution of dentin tubules, microleakage, and bond strength destruction over time. The effect of IDS on the bond strength of indirect restorations is still debatable. This study was conducted to determine the effect of IDS on the bond strength of ceramic restorations to dentin. In this systematic review and meta-analysis, the study protocol was registered on the PROSPERO database under the registration number CRD420202014 27. MEDLINE (PubMed), Web of Science, Scopus, and ProQuest databases were searched until January 2021 and updated in January 2022. Worldcat.org and Opengrey.eu, ProQuest dissertation and thesis, and Google Scholar were searched to explore the grey literature. The in vitro studies evaluating the bond strength of ceramic restoration to dentin with and without IDS were included. Seven criteria were assessed to evaluate the risk of bias in the study. Statistical analyses were conducted using RevMan 5.3. The inverse variance method was used to determine the mean difference of micro-tensile bond strength (µTBS) and shear bond strength (SBS). A total of 10 studies (20 datasets) were included in the meta-analysis. Regarding the µTBS analysis, IDS had a significantly higher bond strength than Delayed Dentin Sealing (DDS) (MD:1.16, 95%CI:0.28_2.03, I2=0%). However, no significant difference was found between them in the SBS analysis (MD:0.25, 95%CI: -0.56-1.06, I2=96%). All studies were categorized to have a moderate or high risk of bias. Most in vitro evidence showed favorable results for the effect of IDS on the bond strength and durability of indirect restorations. The adhesive system and the type of ceramic and its treatment before cementation are determining factors. Due to the heterogeneity of the outcomes and studies with a moderate/high risk of bias, the quality of the evidence was low.

Full Waveform Inversion Based on Dynamic Time Warping and Application to Reveal the Crustal Structure of Western Yunnan, Southwest China

AbstractWe develop a 3D full waveform inversion (FWI) method based on dynamic time warping (DTW) to address the issue of cycle‐skipping, which can prohibit the convergence of conventional FWI methods. DTW globally compares data samples at different time steps in 2D matrices against the time shifts of waveforms. We introduce the concept of shape descriptors into softDTW, creating a soft‐shapeDTW objective function within our waveform inversion process to improve alignment accuracy. Additionally, including constraints from Sakoe‐Chiba bands in the inversion further enhances efficiency and overall performance. A synthetic test has shown that the soft‐shapeDTW inversion outperforms conventional waveform inversions in overcoming the cycle‐skipping challenges that arise from poor initial models. This method was applied to fit observed seismograms to reveal western Yunnan's crustal structure. Seismic waveforms were recorded by 88 broadband stations from 10 local earthquakes, which were then denoised using a continuous wavelet transform method. Generalized cut and paste waveform inversions were used to determine the source parameters of these seismic events. Our inversion well‐aligned various seismic phases in the selected time windows of seismograms, and the resolved velocity models well associate with local geological structure. Results suggest that the soft‐shapeDTW inversion offers a robust alternative to FWI, reducing the reliance on accurate starting models.