quasi-Newton Method Research Articles

Temperature and socioeconomic vulnerability: associations with cardiac event-induced posttraumatic stress symptoms.

Posttraumatic stress symptoms (PTSS) are common after acute coronary syndrome (ACS) and predict increased morbidity and mortality. Climate change contributes to worse mental and cardiovascular health outcomes, thus, PTSS represent a potential mechanism linking climate change to adverse cardiovascular outcomes. Because people living in areas with lower socioeconomic status (SES) experience greater climate vulnerability, have worse cardiovascular health, and may be more susceptible to PTSS, any effect of temperature on PTSS could be amplified in this population. Spatial regression models were estimated to test the association of temperature and temperature variability (within-day variability, directed change over time, and absolute change over time), census tract-level SES, and their interaction with PTSS 1 month post-hospital discharge in a longitudinal cohort study comprising 956 patients evaluated for ACS at an urban U.S. academic medical center between November 2013-May 2017. PTSS were self-reported in relation to the ACS event that brought the patient to the hospital. Census tract-level was computed as a composite score from the CDC Social Vulnerability Index, with higher values indicating lower SES. No temperature or temperature variability metrics were associated with PTSS. Lower census tract-level SES was associated with greater PTSS at 1 month. There was a marginally significant interaction of SES with ACS status, such that we only observed evidence of an association among those with ACS. Temperature exposures were not associated with acute CVD-induced PTSS, which could be a result of a small sample size, mismatched timescale, or lack of a true effect. Conversely, lower census tract-level SES was associated with developing worse PTSS 1 month after evaluation for an ACS. This association appeared stronger in individuals with a true ACS. Early interventions to prevent PTSS could promote better mental and CVD outcomes in this at-risk population.

ID: 215136 Inter-Patient Variability in the Evoked Compound Action Potentials Generated During Spinal Cord Stimulation

A paresthesia-centric closed-loop spinal cord stimulation (SCS) system described recently uses evoked compound action potentials (ECAPs) as a control signal to compensate for spinal cord movement [1]. While ECAP-based SCS has demonstrated clinical efficacy, significant knowledge gaps remain about how the main control variable (i.e., ECAP amplitude) and other metrics (e.g., ECAP threshold (ET), ECAP growth rate) vary across subjects, postures, and pulse widths. These knowledge gaps may complicate the appropriate application of ECAP-controlled, closed-loop SCS. Therefore, in this study, we utilized a combined experimental and computational modeling approach to answer these questions.

0107 Rest-activity rhythmicity across the lifespan: findings from the National Health and Nutrition Examination Survey (NHANES)

Abstract Introduction Non-parametric metrics of interdaily stability (IS), relative amplitude (RA), and intradaily variability (IV) characterize between- and within-day rest-activity rhythms. Prior research has reported differences in these metrics by age and race/ethnicity, but these differences have not been widely assessed in children and adolescents. Therefore, we investigated associations of these metrics with sociodemographic factors across the lifespan, including children, in a US-representative cross-sectional study. Methods Rest-activity metrics were derived from actigraphy data (wrist-worn GT3X+ ActiGraph devices) measured over one week in the 2011-2014 National Health and Nutrition Examination Survey (NHANES). Pregnant participants and participants with < 4 days of valid data were excluded; missing activity data were imputed and pooled using Rubin’s rule. Population-weighted linear and ordinal logistic regression (quartiles) models were fit to examine the associations of age, gender, smoking, body mass index (BMI), income-to-poverty ratio, and self-reported race/ethnicity with rhythmicity measures. Stratified analyses by age groups were conducted. Results There were n=12,526 participants aged 3-80 years. In adjusted analyses, IS and RA (higher: stronger rhythms) decreased with age and were lower among men, whereas IV (higher: weaker rhythm, greater fragmentation) increased with age (p< 0.05). Higher income-to-poverty ratio associated with higher RA (1-unit OR=1.11, 95%CI:1.06,1.16) and IV (1-unit OR=1.10, 95%CI:1.07,1.13). Greater BMI associated with lower RA and IS and higher IV (p< 0.05). Smoking associated with decreased values for all metrics. Compared to the non-Hispanic White group, the Asian, non-Hispanic Black, and Other/Multiracial groups were more likely to have lower RA, lower IS, and higher IV (p< 0.05). Compared to the non-Hispanic White group, the Mexican American (OR=0.83, 95%CI:0.72,0.95) and Other Hispanic (OR=0.83, 95%CI:0.73,0.94) groups were less likely to have higher IV. Analyses stratified by age (≤18, >18 years) resulted in similar patterns among the Asian, non-Hispanic Black, and Other/Multiracial groups (p< 0.05). Conclusion Rest-activity rhythms differ by age, gender, BMI, income, smoking, and race/ethnicity, representing possible windows for public health intervention and sleep health promotion. Differences in rest-activity measures by race/ethnicity begin in childhood, are evident in early adolescence, and persist throughout adulthood. Future analyses will evaluate the contribution of environmental factors to these differences. Support (if any) NIH-NHLBI T32HL007901, R35HL135818

The impact of discriminatory pricing based on customer risk: an empirical investigation using indirect lending through retail networks

PurposeThe purpose of this study is to understand the profit implications of analytics-driven centralized discriminatory pricing at the headquarter level compared with sales force price delegation in the purchase of an aftermarket good through an indirect retail channel with symmetric information.Design/methodology/approachUsing individual-level loan application and approval data from a North American financial institution and segment-level customer risk as the price discrimination criterion for the firm, the authors develop a three-stage model that accounts for the salesperson’s price decision within the limits of the latitude provided by the firm; the firm’s decision to approve or not approve a sales application; and the customer’s decision to accept or reject a sales offer conditional on the firm’s approval. Next, the authors compare the profitability of this sales force price delegation model to that of a segment-level centralized pricing model where agent incentives and consumer prices are simultaneously optimized using a quasi-Newton nonlinear optimization algorithm (i.e. Broyden–Fletcher–Goldfarb–Shanno algorithm).FindingsThe results suggest that implementation of analytics-driven centralized discriminatory pricing and optimal sales force incentives leads to double-digit lifts in firm profits. Moreover, the authors find that the high-risk customer segment is less price-sensitive and firms, upon leveraging this segment’s willingness to pay, not only improve their bottom-line but also allow these marginalized customers with traditionally low approval rates access to loans. This points out the important customer welfare implications of the findings.Originality/valueSubstantively, to the best of the authors’ knowledge, this paper is the first to empirically investigate the profitability of analytics-driven segment-level (i.e. discriminatory) centralized pricing compared with sales force price delegation in indirect retail channels (i.e. where agents are external to the firm and have access to competitor products), taking into account the decisions of the three key stakeholders of the process, namely, the consumer, the salesperson and the firm and simultaneously optimizing sales commission and centralized consumer price.

Joint inversion of two-dimensional magnetotelluric and ambient noise data constrained with cross gradient

We present an alternating joint two-dimensional inversion algorithm for imaging integrated magnetotelluric (MT) and ambient noise dispersion data sets. This approach is based on the limited-memory quasi-Newton method and enforced with cross-gradient constraints that seeks the geometrically similar structural features from multi-geophysical data. A classic synthetic model with same geometric boundaries has been used to test the stability and effectiveness of the joint inversion algorithm. Compared with individual MT and ambient noise tomography (ANT) inversion results, the resistivity and velocity models are captured with higher resolution, especially the electric structures below conductive units are recovered more correctly. The algorithm is also performed on another synthetic example with partial inconsistent boundaries in the resistivity and velocity models more analogous to the realistic scenario. The result demonstrates that, at the inconsistent boundaries, the resistivity model is still imaged correctly but the velocity model is constructed with some artificial structures. We suggest that, in the application of the actual case, the resistivity model obtained from joint inversion is superior and the velocity model should be evaluated comprehensively from individual and joint inversion results.

Minding your steps: a cross-sectional pilot study using foot-worn inertial sensors and dual-task gait analysis to assess the cognitive status of older adults with mobility limitations

BackgroundCognitive impairment is a critical aspect of our aging society. Yet, it receives inadequate intervention due to delayed or missed detection. Dual-task gait analysis is currently considered a solution to improve the early detection of cognitive impairment in clinical settings. Recently, our group proposed a new approach for the gait analysis resorting to inertial sensors placed on the shoes. This pilot study aimed to investigate the potential of this system to capture and differentiate gait performance in the presence of cognitive impairment based on single- and dual-task gait assessments.MethodsWe analyzed demographic and medical data, cognitive tests scores, physical tests scores, and gait metrics acquired from 29 older adults with mobility limitations. Gait metrics were extracted using the newly developed gait analysis approach and recorded in single- and dual-task conditions. Participants were stratified into two groups based on their Montreal Cognitive Assessment (MoCA) global cognitive scores. Statistical analysis was performed to assess differences between groups, discrimination ability, and association of gait metrics with cognitive performance.ResultsThe addition of the cognitive task influenced gait performance of both groups, but the effect was higher in the group with cognitive impairment. Multiple dual-task costs, dual-task variability, and dual-task asymmetry metrics presented significant differences between groups. Also, several of these metrics provided acceptable discrimination ability and had a significant association with MoCA scores. The dual-task effect on gait speed explained the highest percentage of the variance in MoCA scores. None of the single-task gait metrics presented significant differences between groups.ConclusionsOur preliminary results show that the newly developed gait analysis solution based on foot-worn inertial sensors is a pertinent tool to evaluate gait metrics affected by the cognitive status of older adults relying on single- and dual-task gait assessments. Further evaluation with a larger and more diverse group is required to establish system feasibility and reliability in clinical practice.Trial registrationClinicalTrials.gov (identifier: NCT04587895)

Screening for Impaired Glucose Homeostasis: A Novel Metric of Glycemic Control

ObjectiveTo investigate the use of a mathematical model of glucose homeostasis, fit to continuous glucose monitor data, as a metric of dysfunctional glycemic control. Patients and MethodsThree hundred eighty four participants recruited from 2 studies between October 2020 and June 2022 were equipped with a continuous glucose monitor, and interstitial glucose data were automatically collected for 2 weeks. The participants were assessed by a physician and diagnosed as being diabetic, prediabetic, or healthy according to the American Diabetes Association guidelines. A mathematical model of glucose homeostasis was fitted to the glucose data, and model parameter values were obtained. The participants were classified into the following 2 groups on the basis of their glucose homeostasis parameters: effective and impaired. Finally, glycemic variability metrics were compared with glucose homeostasis classification. ResultsThe homeostasis classification resulted in a specificity, sensitivity of individuals with prediabetes, and sensitivity of individuals with type 2 diabetes (T2D) of 0.78, 0.86, and 1.00, respectively, for women and 0.71, 0.86, and 1.00, respectively, for men. This sensitivity was similar to that of glycated hemoglobin A1c measurement (a sensitivity of 0.89 for women and 0.90 for men for prediabetes and a sensitivity of 1.00 for T2D) and superior to that of the oral glucose tolerance test (a sensitivity of 0.18 for women and 0.24 for men for prediabetes and a sensitivity of 0.75 for women and 0.86 for men for T2D). Overall, the individuals classified as impaired had increased glucose variability metrics than the individuals classified as effective (P<.05). ConclusionThe classification of glucose homeostasis on the basis of mathematical modeling of continuous measurements has promising applications as a new metric of dysfunctional glycemic control. Trial Registrationclinicaltrials.gov Identifier: NCT04529239; clinical trial registry identifier: CTRI/2021/08/035957

Identifying the impact of bank competition on corporate shadow banking: Evidence from China

The surge of corporate shadow banking activities in China has drawn much attention from academia and policymakers; yet very little is known about whether bank competition matters for corporate shadow banking activities. Using a large sample of Chinese listed non-financial enterprises (NFEs) over the period of 2003–2019, we identify the impact of bank competition on corporate shadow banking activities. We find a negative relation of bank competition with corporate shadow banking activities. Greater bank competition reduces corporate shadow banking activities by relaxing the firms’ financing constraints, alleviating information asymmetries, and improving their investment efficiency. Our results are robust to alternative metrics of core variables, controlling for regional characteristics, instrumental variable analysis, and the difference-in-differences estimation. Our findings suggest that a deregulation of bank entry, which increases bank competition, is an effective way to restrain corporate shadow banking activities without sacrificing economic growth.

The ventilatory component of the muscle metaboreflex is overstimulated in transthyretin cardiac amyloidosis patients with poor aerobic capacity.

Background: The exercise pressor reflex, i.e., metabo- and mechano-reflex, partially regulates the control of ventilation and cardiovascular function during exercise. Abnormal exercise pressor reflex response has been associated with exaggerated ventilatory drive, sympathovagal imbalance and exercise limitation in chronic heart failure patients. Whether metaboreflex is over-activated and participate to poor aerobic capacity in patients with hereditary transthyretin cardiac amyloidosis (CA-TTR) is unknown. Methods: Twenty-two CA-TTR patients (aged 76 ± 7, 68% male) with the V122I (p.Val142Ile) transthyretin underwent a thorough evaluation including heart rate variability metrics, electrochemical skin conductance (ESC), physical function cardiopulmonary exercise testing, and muscle metaboreflex assessment. Eleven control subjects were chosen for muscle metaboreflex assessment. Results: Age-matched controls (n = 11) and CA-TTR patients (n = 22) had similar metaboreflex sensitivity for heart rate, stroke volume, cardiac index and mean systemic arterial pressure. Compared with age-matched controls, metaboreflex sensitivity for systemic vascular resistance (-18.64% ± 6.91% vs 3.14% ± 23.35%) and minute-ventilation responses (-9.65% ± 14.83% vs 11.84% ± 23.1%) was markedly increased in CA-TTR patients. Values of ESC displayed positive correlations with stroke volume (r = 0.53, p = 0.011) and cardiac index (r = 0.51, p = 0.015) components of metaboreflex sensitivity, an inverse correlation with systemic vascular resistance (r = -0.55, p = 0.008) and a trend with mean arterial (r = -0.42, p = 0.052) components of metaboreflex sensitivity. Peak aerobic capacity (peak VO2%) displayed an inverse correlation with the ventilation component of metaboreflex sensitivity (r = -0.62, p = 0.015). Conclusion: Consistent with the "muscle hypothesis" in heart failure, it is proposed that deterioration of skeletal muscle function in hereditary CA-TTR patients may activate muscle metaboreflex, leading to an increase in ventilation and sensation of breathlessness, the perception of fatigue, and overall sympathetic activation.

Long-term Visit-to-Visit Variability in Hemoglobin A1c and Kidney-Related Outcomes in Persons With Diabetes

To characterize associations between long-term visit-to-visit variability of hemoglobin A1c (HbA1c) and risk of adverse kidney outcomes in patients with diabetes. Observational study. 93,598 adults with diabetes undergoing routine care in Stockholm, Sweden. Categories of baseline and time-varying HbA1c variability score (HVS, the percentage of total HbA1c measures that vary by>0.5% [5.5mmol/mol] during a 3-year window): 0-20%, 21%-40%, 41%-60%, 61%-80%, and 81%-100%, with 0-20% as the reference group. Chronic kidney disease (CKD) progression (composite of>50% estimated glomerular filtration rate [eGFR] decline and kidney failure), acute kidney disease (AKI by clinical diagnosis or transient creatinine elevations according to KDIGO criteria), and worsening of albuminuria. Multivariable Cox proportional hazards regression. Compared with persons showing low HbA1c variability (HVS 0-20%), any increase in variability was associated with a higher risk of adverse kidney outcomes beyond mean HbA1c. For example, for patients with a baseline HbA1c variability of 81%-100%, the adjusted HR was 1.6 (95% CI, 1.47-1.74) for CKD progression, 1.23 [1.16-1.3] for AKI, and 1.28 [1.21-1.36] for worsening of albuminuria. The results were consistent across subgroups (diabetes subtypes, baseline eGFR, or albuminuria categories), in time-varying analyses and in sensitivity analyses including time-weighted average HbA1c or alternative metrics of variability. Observational study, limitations of claims data, lack of information on diet, body mass index, medication changes, and diabetes duration. Higher long-term visit-to-visit HbA1c variability is consistently associated with the risks of CKD progression, AKI, and worsening of albuminuria. The evidence for current guideline recommendations derives from clinical trials that focus on a single HbA1c as the definitive measure of efficacy of an intervention. However, long-term visit-to-visit fluctuations of HbA1c may provide additional value in the prediction of future kidney complications. We evaluated the long-term fluctuations in glycemic control in almost 100,000 persons with diabetes undergoing routine care in Stockholm, Sweden. We observed that higher long-term HbA1c fluctuation is consistently associated with the risks of chronic kidney disease progression, worsening of albuminuria and acute kidney injury. This finding supports a role for long-term glycemic variability in the development of kidney complications and illustrates the potential usefulness of this metric for risk stratification at the bedside beyond a single HbA1c test.

Data-driven airborne bayesian forward-looking superresolution imaging based on generalized Gaussian distribution

Airborne forward-looking radar (AFLR) has been more and more impoatant due to its wide application in the military and civilian fields, such as automatic driving, sea surveillance, airport surveillance and guidance. Recently, sparse deconvolution technique has been paid much attention in AFLR. However, the azimuth resolution performance gradually decreases with the complexity of the imaging scene. In this paper, a data-driven airborne Bayesian forward-looking superresolution imaging algorithm based on generalized gaussian distribution (GGD- Bayesian) for complex imaging scene is proposed. The generalized gaussian distribution is utilized to describe the sparsity information of the imaging scene, which is quite essential to adaptively fit different imaging scenes. Moreover, the mathematical model for forward-looking imaging was established under the maximum a posteriori (MAP) criterion based on the Bayesian framework. To solve the above optimization problem, quasi-Newton algorithm is derived and used. The main contribution of the paper is the automatic selection for the sparsity parameter in the process of forward-looking imaging. The performance assessment with simulated data has demonstrated the effectiveness of our proposed GGD- Bayesian algorithm under complex scenarios.

Dynamic alterations of spontaneous neural activity in post-stroke aphasia: a resting-state functional magnetic resonance imaging study.

The dynamic alterations in spontaneous neural activity of the brain during the acute phase of post-stroke aphasia (PSA) remain unclear. Therefore, in this study, dynamic amplitude of low-frequency fluctuation (dALFF) was applied to explore abnormal temporal variability in local functional activity of the brain during acute PSA. Resting-state functional magnetic resonance imaging (rs-fMRI) data from 26 patients with PSA and 25 healthy controls (HCs) were acquired. The sliding window method was used to assess dALFF, with the k-means clustering method used to identify dALFF states. The two-sample t-test was applied to compare differences in dALFF variability and state metrics between the PSA and HC groups. (1) In the PSA group, greater variance of dALFF in the cerebellar network (CBN) and left fronto-temporo-parietal network (FTPN) was observed. (2) Three dALFF states were identified among all subjects. States 1 and 2 were identified in the PSA patients, and the two dALFF states shared a similar proportion. Moreover, the number of transitions between the two dALFF states was higher in the patients compared with that in HCs. The results of this study provide valuable insights into brain dysfunction that occurs during the acute phase (6.00 ± 3.52 days) of PSA. The observed increase in variability of local functional activities in CBN and left FTPN may be related to the spontaneous functional recovery of language during acute PSA, and it also suggests that cerebellum plays an important role in language.

Quasi newton least mean fourth control for multifunctional grid tied solar photovoltaic system

The quality of power delivered has significantly decreased as distributed energy resources are increasingly incorporated into the current electricity grid. Three-phase voltage source converters with strong and stable control capability are essential for grid-connected solar energy systems. The application of a quasi-newton least mean fourth-based adaptive control strategy for producing the reference grid currents is described in this article. The presented control scheme provides the seamless flow of active and reactive power from the solar system to the grid along with the redressal of significant power quality issues such as harmonic generation at the grid, worsening of power factor, and load unbalancing. The proposed quasi-newton least-mean fourth algorithm aids in effectively filtering the significant lower-order harmonic components. The system is tested under various conditions such as constant irradiance, varying irradiance, and balanced and unbalanced load patterns to demonstrate the robustness and stability of the quasi-newton least-mean fourth algorithm. The simulation results are also presented to illustrate the control strategy's capabilities. dSPACE 1202 controller is utilized for the software-in-loop implementation, and the empirical assessment is verified for both steady-state and dynamic loadconditions.

Multi-Constrained Seismic Multi-Parameter Full Waveform Inversion Based on Projected Quasi-Newton Algorithm

The multi-parameter full waveform inversion (FWI) that integrates velocity and density can make full use of the kinematic and dynamic information of the measured data to reconstruct the underground model. However, it faces problems of crosstalk between multiple parameters and strong nonlinearity. This research proposes a multi-constrained, multi-parameter FWI framework based on the projected quasi-Newton algorithm. This framework can introduce multiple types of prior geological information, which can effectively improve the problem of multi-parameter inversion. Additionally, the quasi-Newton method can eliminate the crosstalk phenomenon to further improve the inversion convergence speed. Taking the 1994BP model as an example, the results show that the projected quasi-Newton method has a faster convergence speed than the spectral projected gradient method, and reduces the crosstalk between parameters; multiple constraint sets are uniquely projected onto the intersection to ensure that the estimated values of model parameters meet multiple constraints. We also experiment with the overthrust model, which shows that the framework we proposed can improve the inversion accuracy and has good adaptability. The proposed multi-parameter inversion framework can be compatible with more prior information to obtain an inversion model that conforms to geological understanding and shows great potential in seismic exploration.

“A comprehensive assessment of suitability of Global Precipitation Products for hydro-meteorological applications in a data-sparse Himalayan region”

Observation rainfall networks in developing countries such as Nepal face many challenges (like availability and quality). Global Precipitation Products (GPPs) could be an alternative to gauge-based observed rainfall (GOR) in hydro-meteorological studies. However, GPPs performance across the Himalayan regions is still unknown and is influenced by several factors such as spatial and temporal resolutions, primary data sources, etc. We have comprehensively assessed the suitability of the latest GPPs using categorical and continuous variable performance metrics for the Gandak River Basin in the Nepalese Himalayas. We then ranked GPPs for the first time using the Multicriteria Decision-Making technique. 11 out of 12 GPPs considered underestimated the annual rainfall in the basin. Performance of GPPs was also inconsistent for monthly/annual and daily timescales. At longer timescales, CHIRPS and IMERG_Final are better at representing the spatial and temporal pattern of the rainfall (spatial correlation of 0.75) and least percentage bias (PBIAS < 12%). At a daily timescale, IMERG_Final, ERA5, and PERSIANN_CDR stand out for probability of detection (POD) of rainfall, while all GPPs perform poorly in false alarm ratio (FAR). Although all GPPs have relatively high RMSE (6-14 mm/day), correlation (CC) with observed rainfall was high for IMERG_Final, ERA5, and MERRA_2 in most of the sub-basins. With elevation, the performance of all GPPs is reduced, as evidenced by higher PBIAS, and lower CC. Although there is plenty of room for improvements in rainfall estimation by GPPs, among the existing dataset, IMERG_Final scored best in the majority of the performance indicators and ranked first in five out of six sub-basins. It would be relatively the better choice in the data sparse Himalayan region when daily rainfall data is required. For applications that require monthly/annual rainfall, both CHIRPS and IMERG_Final are equally suitable. The method proposed in the study for assessing GPPs can be readily applied in other river basins and at sub-daily timescales.

0954 CORRELATION OF PULSE RATE VARIABILITY (PRV) AND HEART RATE VARIABILITY (HRV) METRICS DURING SLEEP IN SUBJECTS SUSPECTED OF OSA

Abstract Introduction Whether photoplethysmography (PPG)-derived pulse rate variability (PRV) metrics can be surrogates for ECG-derived heart rate variability (HRV) is a decade-long debate. Very few studies have assessed the performance of PRV metrics in wearables. We aimed to evaluate the performance of time- and frequency-domain PRV metrics derived from the Belun Ring (BR) in subjects suspected of sleep apnea. Methods Using Pearson’s correlation coefficient (PCC), we retrospectively analyzed the relationship between concurrent BR-PRV and PSG ECG-HRV metrics (standard deviation of NN intervals [SDNN], root mean square of successive RR interval differences [RMSSD], percentage of successive RR intervals that differ by more than 50 ms [PNN50], HF [high frequency] power, LF [low frequency] power, VLF [very low frequency] power, and LF/HF ratio) in 73 subjects suspected of OSA. Subgroup analyses were performed based on demographic information, OSA, co-morbidities, and HR-affecting medication status. Results Age (SD) 50.1 (13.4); female 68%; black 52%; BMI (SD) 36.1 (9.7); 56% OSA; mean AHI (SD) 14.7 (17.3). Nine (12%) subjects had significant arrhythmias (defined as having any arrhythmias in ≥25% of all 12-second segments.) Key findings: There was a unitary linear relationship between BR PPG-pulse rate and ECG-heart rate in the overall group. In those without significant arrhythmias (N=64), PRV-SDNN, PNN50, HF, LF, and VLF had excellent correlations (PCC ≥0.90) with corresponding HRV metrics in all subgroups. PRV-RMSSD and PRV-LF/HF also had a strong correlation (PCC ≥0.80) with ECG HRV-RMSSD and HRV-LF/HF in all subgroups except for LF/HF in the diabetes group. In those with significant arrhythmias (N=9), PRV performed less well, with most metrics having PCC &amp;lt; 0.90 or wide CI, except for PNN50. All PRV metrics had PCCs ≥0.90 in subjects on HR-affecting medications except for LF/HF. Conclusion BR-PRV metrics can serve as surrogates for ECG-HRV in patients suspected of OSA who do not have significant arrhythmias. PRV-RMSSD and LF/HF may be less robust than the rest of the PRV metrics but still showed strong correlations in most subgroups. BR-PRV can be a useful clinical and research tool in assessing autonomic nervous system function. Support (if any) This study is supported by a Grant from Belun Technology Company

Rapid Estimation of Sulfur Content in High-Ash Indian Coal Using Mid-Infrared FTIR Data

High-ash Indian coals are primarily used as thermal coal in power plants and industries. Due to the presence of sulfur in thermal coal, flue gas is a major environmental concern. Conventional methods (Ultimate Analysis of Coal) for sulfur content estimation are time-consuming, relatively costly, and destructive. In this study, Fourier-transform infrared (FTIR) spectroscopy has emerged as a promising alternative method for the rapid and nondestructive analysis of the sulfur content in coal. In the present study, the actual sulfur content in the coal samples was determined using Ultimate Analysis (CHNS analyzer). In contrast, mid-infrared FTIR spectroscopic data (4000–400 cm−1) were used to analyze the functional groups related to sulfur or its compounds in the coal samples to predict the sulfur content. A comparison of sulfur estimated using a CHNS analyzer and predicted using mid-infrared spectroscopy (FTIR) data shows that it can accurately predict sulfur content in high-ash Indian coals using the piecewise linear regression method (Quasi-Newton, QN). The proposed FTIR-based sulfur prediction model showed a coefficient of determination (R2) of up to 0.93, where the total no. of samples (Coal + KBr pellets, n) was 126 (using 17:1 split, K-fold cross validation). The root-mean-square error (RMSE, wt.%) is 0.0035, mean bias error (MBE, wt.%) is −0.0003, MBE (%) is 3.31% and mean absolute error (MAE, wt.%) is 0.0020. The two-tailed t-test and F-test for mean and variance indicated no significant difference between the pair of values of observed sulfur (SCHNS, wt.%) using CHNS data and the model predicted sulfur (SFTIR, wt.%) using FTIR data. The prediction model using mid-infrared FTIR spectroscopy data and the Quasi-Newton method with a breakpoint and loss function performs well for coal samples from the Johilla Coalfield, Umaria. Thus, it can be a valuable tool for analyzing sulfur in other ash-rich coals from various basins worldwide.

Electromagnetic Fields - Do They Pose a Cardiovascular Risk?

Mobile wireless communication technologies have now become an everyday part of our lives, 24 hours a day, 7 days a week. Monitoring the autonomous system under exposition to electromagnetic fields may play an important role in broading of our still limited knowledge on their effect on human body. Thus, we studied the interaction of the high frequency electromagnetic field (HF EMF) with living body and its effect on the autonomic control of heart rate using Heart Rate Variability (HRV) linear and nonlinear analyses in healthy volunteers. A group of young healthy probands (n=30, age mean: 24.2 ± 3.5 years) without any symptoms of disease was exposed to EMF with f=2400 MHz (Wi Fi), and f=2600 MHz (4G) for 5 minutes applied on the chest area. The short-term heart rate variability (HRV) metrics were used as an indicator of complex cardiac autonomic control. The evaluated HRV parameters: RR interval (ms), high frequency spectral power (HF-HRV in [ln(ms2)]) as an index of cardiovagal control, and a symbolic dynamic index of 0V %, indicating cardiac sympathetic activity. The cardiac-linked parasympathetic index HF-HRV was significantly reduced (p =0.036) and sympathetically mediated HRV index 0V % was significantly higher (p=0.002) during EMF exposure at 2400 MHz (Wi-Fi), compared to simulated 4G frequency 2600 MHz. No significant differences were found in the RR intervals. Our results revealed a shift in cardiac autonomic regulation towards sympathetic overactivity and parasympathetic underactivity indexed by HRV parameters during EMF exposure in young healthy persons. It seems that HF EMF exposure results in abnormal complex cardiac autonomic regulatory integrity which may be associated with higher risk of later cardiovascular complications already in healthy probands.

Determination of a Nonlinear Coefficient in a Time-Fractional Diffusion Equation

In this paper, we study direct and inverse problems for a nonlinear time fractional diffusion equation. We prove that the direct problem has a unique weak solution and the solution depends continuously on the coefficient. Then we show that the inverse problem has a quasi-solution. The direct problem is solved by the method of lines using an operator approach. A quasi-Newton optimization method is used for the numerical solution to the inverse problem. The Tikhonov regularization is used to overcome the ill-posedness of the inverse problem. Numerical examples with noise-free and noisy data illustrate the applicability and accuracy of the proposed method to some extent.

Impact of cognitive exertion on autonomic reactivity in individuals with persistent post-concussive symptoms (P7-1.010)

<h3>Objective:</h3> Examine the impact of cognitive exertion on autonomic reactivity in symptomatic and asymptomatic individuals with history of concussion and controls without history of concussion. <h3>Background:</h3> Following concussive head injuries, many individuals continue to experience physical, cognitive, and emotional symptoms that can persist for months or years. Recent studies suggest that concussive head injuries can also produce persistent dysfunction of the autonomic nervous system. However, it remains unclear if acute bouts of cognitive exertion moderate autonomic dysfunction in individuals with persistent post-concussion symptoms. <h3>Design/Methods:</h3> A cross-sectional design was used to investigate autonomic reactivity in 23 individuals without history of concussion (HC-) and 35 individuals with history of concussion, including 20 symptomatic (HCx-S) and 15 asymptomatic (HCx-A). Participants were classified based on clinical history and symptom reports obtained from a comprehensive questionnaire of their medical history and the Rivermead Post-Concussion Questionnaire (RPQ). Participants initially completed a seated, six-minute resting assessment with eyes open in the dimly lit room. They then completed a continuous reaching variant of the traditional Go/NoGo task. Continuous electrocardiography was recorded and utilized to compute time-domain metrics of heart rate variability (HRV) during the resting assessment and cognitive task. <h3>Results:</h3> HCx-S participants reported greater symptom burden on the RPQ and performed significantly worse on the Go/NoGo task compared to HC- and HCx-A participants. While HRV metrics failed to reveal any significant differences between HCx-S, HCx-A, and HC-participants during resting assessment (p’s &gt; 0.8), HCx-S participants exhibited significantly greater HRV than HCx-A and HC-participants during the Go/NoGo task (p’s &lt; 0.03). <h3>Conclusions:</h3> Increased HRV in HCx-S participants compared to HC- and HCx-A participants during the Go/NoGo task indicates that concussion may induce greater autonomic reactivity, characterized by higher levels of vagal/parasympathetic tone. This may reflect impairments in the capacity of the autonomic nervous system to efficiently adapt to situational demands. <b>Disclosure:</b> Dr. Moore has nothing to disclose. Taylor Marie Wynne has nothing to disclose. Dr. Broglio has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for MCW. Dr. Broglio has received personal compensation in the range of $0-$499 for serving as a Consultant for U Calgary. Dr. Broglio has received personal compensation in the range of $5,000-$9,999 for serving as an Expert Witness for Montgomery McCracken Walker &amp; Rhoads LLP. The institution of Dr. Broglio has received research support from DoD. The institution of Dr. Broglio has received research support from NCAA. The institution of Dr. Herter has received research support from Woodcock Institute. The institution of Dr. Herter has received research support from National Institutes of Health. The institution of Dr. Herter has received research support from National Institutes of Health. The institution of an immediate family member of Dr. Herter has received research support from Centers for Disease Control and Prevention.