General Modeling Approach Research Articles

Schiff Bases: A Captivating Scaffold with Potential Anticonvulsant Activity.

One of the most important organic compounds, also known as a Schiff base, imine, or azomethine, has been associated with several biological processes. The group is a component of both natural or synthetic chemicals and functions as both a precursor and an intermediary in the synthesis of therapeutically active substances. The review highlights the various non-metal Schiff bases' structure-activity relationship (SAR) studies, general model, docking, and design approach for anticonvulsant actions. Schiff bases serve as linkers in numerous synthetic compounds with a variety of activities, according to the findings of several investigations. As a result, the current review will give readers a thorough understanding of the key ideas put forth by different researchers regarding the anticonvulsant properties of Schiff bases. It will serve as a valuable information source for those planning to synthesize new anticonvulsant molecules that contain Schiff bases as pharmacophores or biologically active moieties.

Determination of morphine sulfate anti-pain drug solubility in supercritical CO2 with machine learning method

Accurate solute solubility measuring and modeling in supercritical carbon dioxide (ScCO2) would address the best working conditions and thermodynamic boundaries for material processing with this type of fluid. Theory- and data-driven methods are two general modeling approaches. Using theory-driven methods, the solubility is estimated based on the principles of thermodynamics, while data-driven methods are developed by training the algorithms. Despite acceptance of each of these methods, more experimental solubility data are still needed to promote modeling performances. In this study, for the first time, solubility of morphine sulfate is determined and modeled by a set of 13 semi-empirical (theory-driven) and random forest (data-driven) models. Using a laboratory system with an ultraviolet-visible (UV-Vis) spectroscopy, the experimental solubilities including 48 data points were obtained at different temperatures (308–338 K) and pressures (12–27 MPa). The minimum (0.806 × 10−5) and maximum (5.902 × 10−5) equilibrium mole fractions were observed at working pressures of 12 and 27 MPa, respectively, both at the same temperature of 338 K. It was indicated that random forest model (with AARD% of 1.29%) had an excellent predictive performance against semi-empirical models (with AARD% from 9.33 to 19.76%). The results showed that solute molecular weight had the highest effect on random forest modeling. Using modeling results from Chrastil and Bartle models, total and vaporization enthalpies of dissolution of morphine sulfate in ScCO2 were found to be 35.12 and 59.04 kJ/mole, respectively.

A newly integrated model for synthesizing multiple external forcing signals to predict the ridge line of the western North Pacific subtropical high in summer

The western North Pacific subtropical high (WNPSH) is a critical atmospheric circulation system influencing weather and climate patterns in eastern China. Accurately predicting its activity is essential for anticipating and managing natural disasters such as droughts and floods in the region. In this study, we employ the decision tree (DT) as the fundamental model and devise a compatible framework to create an integrated model known as the Decision Tree Integration Model for Synthesizing Multiple External Forcing Signals (DTI-MS), to perform classification prediction of the WNPSH ridge line in summer. Within the construction of DTI-MS, the interpretability advantage of DT model is fully exploited. Three significant sources of external forcing signals, namely sea surface temperature in the Pacific, Tropical Indian Ocean and Atlantic Ocean, and snow depth across the Eurasian continent, are identified from distinct DT models, with clear physical meanings. Through the voting strategy, these signals are integrated, laying the groundwork for DTI-MS to synthesize multiple external forcing signals. Regarding prediction performance, DTI-MS achieves a high classification accuracy of 91% in the training set and 93% in the testing set, with recalls for the southerly and northerly positions of the WNPSH in the testing set also exceeding 80%. Compared with the commonly used machine learning models such as DT and Random Forests constructed through general modeling approaches, DTI-MS also demonstrates higher classification accuracy. Overall, DTI-MS not only shows promising potential in predicting the WNPSH ridge line, but its integration framework also provides a new paradigm for short-term climate prediction modeling.

Admittance-based equivalent circuit modeling of multi-patch piezoelectric energy harvesting plate

Abstract Harvesting energy from mechanical vibration using piezoelectric material is a common method to power small electronics and batteries. Implementation of multiple piezo-patches to plate-like structures increases the power capacity and frequency bandwidth of the energy harvester since multiple patches can capture more vibrational modes of the dense plate dynamics. To optimize the harvested electrical output using advanced harvesting circuits, equivalent circuit modeling (ECM) is a useful technique for representing the entire electromechanical system in circuit- simulator-software (LTspice). The ECM technique based on finite-element (FE) simulation has been used for plate-like structures with only one single-piezo-patch-harvester in the literature. However, when multiple patches are integrated into a plate-like structure, their coupling can cause charge cancelation, resulting in complex dynamics that cannot be handled by the existing ECM methods. This paper presents three new methodologies for extracting a multi-mode ECM of the harvesters (e.g.: multi-patch piezo-harvesters integrated into a plate), using an admittance-based system identification approach utilizing FE results. The first method incorporates the ECM of multi-patch harvester into a single ECM, so called OGC. It includes a circuit branch where multiple patches have only one ECM branch for each vibration mode, which requires less equivalent circuit elements and hence less computational cost. The second and third so-called respective ground uncoupled (RGU) and respective ground coupled (RGC) ECM methods generate circuit branches for each piezo-patch and for each vibration mode, whereby their electrical connection (e.g. parallel or series) is later configured in LTspice. The RGU method provides a general multi-patch modeling approach while RGC method provides ECM parameters for each patch simultaneously when they are all connected which is the case in network harvester analysis. The ECMs of parallel multi-patch harvesters are validated by system-level FE simulations. The proposed admittance-based ECM methods are reliable for deriving the system parameters of multi-patch harvesters.

Bloch equations in terahertz magnetic-resonance ellipsometry

A generalized approach derived from Bloch's equation of motion of nuclear magnetic moments is presented to model the frequency, magnetic field, spin density, and temperature dependencies in the electromagnetic permeability tensor for materials with magnetic resonances. The resulting tensor model predicts characteristic polarization signatures which can be observed, for example, in Mueller matrix element spectra measured. When augmented with thermodynamic considerations and suitable Hamiltonian description of the magnetic eigenvalue spectrum, important parameters such as density, spectral amplitude distribution, relaxation time constants, and geometrical orientation parameters of the magnetic moments can be obtained from comparing the generalized model approach to experimental data. We demonstrate our approach by comparing model calculations with full Mueller matrix element spectra measured at an oblique angle of incidence in the terahertz spectral range, across electron spin resonance quintuplet transitions observed in wurtzite-structure GaN doped with iron. Our model correctly predicts the complexity of the polarization signatures observed in the 15 independent elements of the normalized Mueller matrix for both positive and negative magnetic fields and will become useful for future analysis of frequency and magnetic field-dependent magnetic resonance measurements. Published by the American Physical Society 2024

A survey of the application and technical improvement of the multi-armed bandit

In recent years, the multi-armed bandit (MAB) model has been widely used and has shown excellent performance. This article provides an overview of the applications and technical improvements of the multi-armed bandit machine problem. First, an overview of the multi-armed bandit problem is presented, including the explanation of a general modeling approach and several existing common algorithms, such as -greedy, ETC, UCB, and Thompson sampling. Then, the real-life applications of the multi-armed bandit model are explored, covering the fields of recommender systems, healthcare, and finance. Then, some improved algorithms and models are summarized by addressing the problems encountered in different application domains, including the multi-armed bandit considering multiple objectives, the mortal multi-armed bandits, the multi-armed bandit considering contextual side information, combinatorial multi-armed bandits. Finally, the characteristics, trends of changes among different algorithms, and applicable scenarios are summarized and discussed.

Model-Based Adaptive Control of Bioreactors—A Brief Review

This article summarizes the authors’ experiences in the development and application of the General Dynamical Model Approach related to adaptive linearizing control of biotechnological processes. Special attention has been given to some original, innovative solutions in model-based process control theory: new formalization of biotechnological process kinetics, derivation and tuning of the general software sensor of the full kinetics of biotechnological processes, and a general algorithm for fully adaptive linearizing control with software sensors. These theoretical solutions are the basis of three control strategies—fully adaptive control of the main substrate, partially adaptive control of intermediate metabolite, and recognition and stabilization of the desired physiological state based on the proposed theoretical solutions. Each strategy is illustrated in different case studies. The advantages and limitations of each of them are identified and discussed. The derived algorithms for monitoring and controlling the considered biotechnological processes are realized and included in a software platform named Interactive System for Education in Modelling and Control of Bioprocesses (InSEMCoBio). The InSEMCoBio modules and their main functions are discussed. The effectiveness of the proposed control strategies (achieving maximum productivity) has been proven through a series of simulation investigations of the considered case studies.

Brain state dynamics differ between eyes open and eyes closed rest.

The human brain exhibits spatio-temporally complex activity even in the absence of external stimuli, cycling through recurring patterns of activity known as brain states. Thus far, brain state analysis has primarily been restricted to unimodal neuroimaging data sets, resulting in a limited definition of state and a poor understanding of the spatial and temporal relationships between states identified from different modalities. Here, we applied hidden Markov model (HMM) to concurrent electroencephalography-functional magnetic resonance imaging (EEG-fMRI) eyes open (EO) and eyes closed (EC) resting-state data, training models on the EEG and fMRI data separately, and evaluated the models' ability to distinguish dynamics between the two rest conditions. Additionally, we employed a general linear model approach to identify the BOLD correlates of the EEG-defined states to investigate whether the fMRI data could be used to improve the spatial definition of the EEG states. Finally, we performed a sliding window-based analysis on the state time courses to identify slower changes in the temporal dynamics, and then correlated these time courses across modalities. We found that both models could identify expected changes during EC rest compared to EO rest, with the fMRI model identifying changes in the activity and functional connectivity of visual and attention resting-state networks, while the EEG model correctly identified the canonical increase in alpha upon eye closure. In addition, by using the fMRI data, it was possible to infer the spatial properties of the EEG states, resulting in BOLD correlation maps resembling canonical alpha-BOLD correlations. Finally, the sliding window analysis revealed unique fractional occupancy dynamics for states from both models, with a selection of states showing strong temporal correlations across modalities. Overall, this study highlights the efficacy of using HMMs for brain state analysis, confirms that multimodal data can be used to provide more in-depth definitions of state and demonstrates that states defined across different modalities show similar temporal dynamics.

Prothrombin and activated partial thromboplastin times, thromboelastography, hematocrit, and platelet count in a feline hemorrhage/over-resuscitation model using lactated Ringer's solution or 6% tetrastarch 130/0.4.

To describe and compare prothrombin time (PT), activated partial thromboplastin time (aPTT), thromboelastography (TEG), HCT, and platelet count measurements in a hemorrhage/over-resuscitation model. Randomized crossover study. University teaching hospital. Six cats. Anesthetized cats underwent 3 treatments at 2-month intervals. The treatments were as follows: NHR-no controlled hemorrhage and sham resuscitation; LRS-controlled hemorrhage and lactated Ringer's solution (LRS) for resuscitation; and Voluven-controlled hemorrhage and 6% tetrastarch 130/0.4 for resuscitation. The LRS and Voluven were administered at 60 and 20mL/kg/h, respectively, for 120minutes. Blood samples were drawn for PT, aPTT, TEG, HCT, and platelet count measurements at a healthy check (T - 7d), after controlled hemorrhage (T0), at 60 and 120minutes of resuscitation (T60 and T120), and at 24hours after completion of resuscitation (T24h). Data were analyzed using a general linear mixed model approach (significance was P<0.05). Total median blood loss (controlled hemorrhage and blood sampling from T0 to T120) at T120 was 11.4, 31.0, and 30.8mL/kg for NHR, LRS, and Voluven, respectively. PT and aPTT during LRS and Voluven were prolonged at T60 and T120 compared to NHR (P<0.001). On TEG, the reaction time, kinetic time, and alpha-angle were within reference intervals for cats at all time points in all treatments, while maximum amplitude was less than the reference interval (40mm) at T0, T60, and T120 during Voluven and at T60 and T120 during LRS compared to NHR (both P<0.001). The HCT and platelet count were significantly lower at T60 and T120 during LRS and Voluven compared to NHR (P<0.001). Hypocoagulopathy was observed during hemorrhage and liberal fluid resuscitation. Prolongation of PT and aPPT and decreased clot strength may have been caused by hemodilution and platelet loss.

Factors Affecting Postpartum Bone Mineral Density in a Clinical Trial of Vitamin D Supplementation.

Background: Few studies evaluate the effects of vitamin D status and supplementation on maternal bone mineral density (BMD) during lactation and further lack inclusion of diverse racial/ethnic groups, body mass index (BMI), or physical activity. Objective: Determine the effects of vitamin D treatment/status, feeding type, BMI, race/ethnicity, and physical activity on postpartum women's BMD to 7 months. Methods: Women with singleton pregnancies beginning 4-6 weeks' postpartum were randomized into two treatment groups (400 or 6400 IU vitamin D/day). Participant hip, spine, femoral neck, and whole-body BMD using Dual-energy X-ray absorptiometry (DXA Hologic), serum 25-hydroxyvitamin D [25(OH)D] (RIA; Diasorin), BMI, and physical activity were measured at 1, 4, and 7 months postpartum. A general linear mixed modeling approach was undertaken to assess the effects of vitamin D status [both serum 25(OH)D concentrations and treatment groups], feeding type, race/ethnicity, BMI, and physical activity on BMD in postpartum women. Results: During the 6-month study period, lactating women had 1-3% BMD loss in all regions compared with 1-3% gain in nonlactating women. Higher maternal BMI was associated with less bone loss in femoral neck and hip regions. Black American women had less BMD loss than White/Caucasian or Hispanic lactating women in spine and hip regions. Exclusively breastfeeding women in the 6400 IU vitamin D group had less femoral neck BMD loss than the 400 IU group at 4 months sustained to 7 months. Physical activity was associated with higher hip BMD. Conclusion: While there was BMD loss during lactation to 7 months, the loss rate was less than previously reported, with notable racial/ethnic variation. Breastfeeding was associated with loss in BMD compared with formula-feeding women who gained BMD. Higher BMI and physical activity independently appeared to protect hip BMD, whereas higher vitamin D supplementation appeared protective against femoral neck BMD loss.

Streamflow prediction in ungauged basins: How dissimilar are drainage basins?

Hydrological processes leading to flow in river channels are extremely complex, which is why we cannot use any fundamental law to fully explain river flow dynamics at basin scale. The general approach for hydrological modelling considers that every catchment’s response to precipitation input is unique, which means different catchments respond differently to the same precipitation input. In other words, river basins are sufficiently dissimilar to warrant having hydrological models with multiple free-parameters for predicting discharge. It is assumed that free-parameters are related to static catchment characteristics. However, past efforts to relate model parameters with observable catchment characteristics have not been very successful. We thus need a framework to quantify catchment dissimilarities exhibited by catchment characteristics because there is no need of free-parameters if we decide to ignore dissimilarities. Thus, the relative roles of climate and catchment characteristics in the streamflow response of the basin needs to be quantified. In this study, we have considered daily data from 3534 gauging stations spread across the globe to compare HBV, a widely used hydrological model, with Dynamic Budyko (DB) model, a recently proposed calibration-free model. The HBV model assumes that both climate and catchment characteristics are important in modeling streamflow response, whereas a calibration-free DB model essentially assumes that streamflow response is largely governed by climate. The performance of HBV run with regionalized parameters and DB in terms of median coefficient of determination (R2) and weighted R2 (WR2) are (0.43, 0.45) and (0.24, 0.27), respectively. The corresponding values of R2 and WR2 from quantile-quantile comparison are (0.94, 0.94) and (0.60, 0.59). The results here seem to support the idea of developing calibration-free models by appreciating similarities between basins, particularly if the objectives are prediction in ungauged basins and assessment of climate change impact on streamflow.

Impact Dynamics Simulation for Magnetorheological Fluid Saturated Fabric Barriers

Abstract Experimental research has investigated the non-Newtonian fluid augmentation of fabric barrier materials, aimed at adding impact energy dissipation mechanisms and thereby improving ballistic performance. Published experimental results on the effectiveness of these augmentations are mixed, and numerical models supporting complimentary modeling research are lacking, primarily due to the multiple geometric and material nonlinearities present in the system. The combination of Hamiltonian mechanics with hybrid particle-element kinematics offers a very general modeling approach to impact simulation for these systems, one which includes interstitial fluid–structure interactions, the yarn level dynamics of projectile impacts, and yarn fracture without the introduction of slidelines and without mass or energy discard. Three-dimensional (3D) impact simulations show good agreement with published experiments for magnetorheological (MR) fluid-saturated Kevlar, including fabric tested under bulk field excitation of the target region and magnetomechanically edge-clamped fabric sliding in an excited air gap. The Hamiltonian method employed to develop the system-level model allows for computationally efficient partitioning of the modeled physics while maintaining a thermodynamically consistent formulation.

Interactions at the interfaces of the H2-brine-cement systems at elevated pressures for H2 storage

There is a global demand on assessment of potential subsurface gas storage sites in view of safely injecting hydrogen or carbon dioxide. One relevant aspect that has already been subject to thorough investigation is the mutual interaction of all participating compounds in terms of the wetting behaviour that on its turn is directly related to the predominating capture mechanisms. Given the diversity of the geophysical and geochemical circumstances, transferability of results from work conducted on one geological site to another location is limited. For instance, there is a large number of publications on wettability of many different rock types in hydrogen atmosphere that are partly controversal and strictly applicable only to the respective reported system. Hence, there is a gap in finding general model approaches that serve for a holistic understanding of predominating mechanisms and building the fundamentals for predicting the behaviour of systems that have not been studied so far. The presented work addresses this gap by quantifying mutual interactions of the participating phases in a solid-liquid-gas systems and determining the respective interfacial tensions, γSV (solid-vapor), γLV, (liquid-vapor) and γSL (solid-liquid).Neumann and Good demonstrated how to determine the solid-fluid interfacial tension based on the contact angle and the liquid-gas interfacial tension by calculating a so-called molecular interaction parameter. Up to date, this method has been applied, among others, for systems containing CO2 and solids such a teflon, glass, and steel. The methodology could be confirmed by testing systems comprising steel - H2O - CH4 /H2 and comparing the results to the aforementioned literature data.As one of the critical parts in H2 underground storage, the completion system containing a common well cement, H2 and brine was subject to this work. The interfacial tension between H2 and brine as well as the contact angle between the fluid phases and the cement were investigated experimentally up to 20 MPa, temperatures from 313.15 to 353.15 K and NaCl – concentrations of up to 10% wt. As a theoretical approach, the interfacial tension of the system H2O+H2 was investigated using the density gradient theory (DGT) in combination with the perturbed chain statistical associating fluid theory equation of state (PC-SAFT). Finally, the H2-cement interfacial tension is determined through the calculation of a so-called molecular interaction parameter. The interfacial tension data of H2O+H2 experimentally and theoretically determined in this work agree among each other as well as with previous literature data. Likewise, agreement was found between the brine+H2 interfacial tension and previous studies. The contact angle appears to be influenced mostly by pressure, producing a less H2O/brine-wet system as pressure increases. The H2-cement interfacial tension decreases from approximately 150 mN/m down to 100 mN/m, as the pressure increases from 0.1 to 20 MPa. The presented data suggest H2 to be slightly adsorbed on the one hand but the capillary entry pressure to decrease on the other, causing concerns regarding the integrity of the completion system.

Fiscal Policy for Inclusive Growth. A Case Study of Myanmar

Following decades of isolation under military rule, Myanmar initiated historic political reforms since 2011, but faces challenges translating liberalization into broad-based advancement. A dynamic stochastic general equilibrium modelling approach estimated on Myanmar data is used, with simulations quantifying potential growth and distributional impacts of strategic government expenditure reallocations towards infrastructure upgrading, agricultural investments, expanded social transfers and progressive tax reforms. Results indicate sustained infrastructure and rural productivity spending have high output multipliers while well-targeted transfers reduce income inequality. However, institutional absorptive capacities condition realization of social returns. Complementary governance enhancements like project oversight and competitiveness in public investment allocation prove vital. Regional peer benchmarking provides comparative lessons. Altogether, evidence-based fiscal reorientation towards addressing pressing human capital, rural-urban and firm competitiveness constraints can accelerate inclusive growth in Myanmar if pursued prudently. Sustainable expansion requires strengthening public financial management (PFM) systems and results monitoring.

The problems of macroeconomics as institutional problems: complementing the ‘what went wrong’ story with a social epistemology perspective

Abstract After the financial crisis of 2008, many economists expressed dissatisfaction with the state of macroeconomics. They criticised deficiencies in the dominant dynamic stochastic general equilibrium modelling approach and conceptions of good macroeconomic research behind that dominance. This paper argues that there is a deeper problem in macroeconomics, which remains unaddressed. I connect existing literature critical of the institutions of macroeconomics and of economics in general to the institutional preconditions of effective criticism outlined by the philosopher Helen Longino. I find that as an epistemic community, macroeconomics does not function in a way that adequately supports critical evaluation of established beliefs, norms and practices. This failure may partly explain why many views on macroeconomic modelling, the tenability of which economists questioned after the crisis, were able to persist for so long. My analysis gives additional support to several recent proposals for institutional reforms in economics.

A Historical Plankton Index: Zooplankton abundance in the North Sea since 800 CE

The North Sea region boasted one of the world’s most important fisheries for many centuries. Climate directly and indirectly influences the development and survival of many important pelagic fish in the North Sea ecosystem. One indirect influence is the food availability in the form of phyto- and zooplankton abundance, which is strongly controlled by environmental factors. One of these environmental factors is local sea surface temperatures. A negative correlation between zooplankton abundance and sea surface temperature is well established for the epeiric sea on the European continental shelf. Continuous temporal observations of North Sea zooplankton production only exist since 1958. Therefore we developed a Historical Plankton Index (HPI) from 800 CE onwards to extend our record of temperature-driven zooplankton abundance in the North Sea over a multi-centennial time scale. For this we used the North Atlantic temperature reconstructions and associations between zooplankton abundance and contemporary sea surface temperatures established applying a General Additive Modelling (GAM) approach. We then examined the association between the HPI and historical landings from the Dutch commercial herring fishery in the 17th century to test the utility of our HPI. We examine the potential influence of food availability (in terms of zooplankton abundance) on the fishery, the evolution of which is often only considered in terms of human influences such as conflict, fishing gear and demand for fish as a commodity. We find that under certain conditions the HPI can explain 20% of the variability in Dutch herring landings. This highlights the importance of developing long-term and large-scale indices of natural marine ecosystem dynamics to understand the historical fortunes of the commercial fishing industry. The results are directly relevant to the United Nations’ sustainable development goal 14 – life below water.

The efficacy of spatio‐temporal predictors in forecasting the risk of Cydia nigricana infestation

AbstractThe ability to estimate the risk of pest infestation can help farmers to reduce pesticide application and provide guidance that would result in better management decisions. This study tested whether different combinations of spatial and temporal risk factors may be used to predict the damage potential of pea moth, Cydia nigricana Fabricius (Lepidoptera: Tortricidae), a major pest in field pea (Pisum sativum L., Fabaceae). Over four consecutive years, the abundance of pea moth was monitored by placing pheromone traps at various field pea‐cultivation sites. We also assessed the phenological development stages and the percentage of damaged seeds per 100 pods collected from each growing pea field in a region of approximately 30 km in diameter. The study found the significant infestation risk indicators to be the time of flowering, the date on which male pea moths are first detected in the monitoring traps and the minimum distance to pea fields that were planted and harvested in the previous growing season. The combination of all three factors using a general additive model approach yielded the best results. The model proposed by this study accurately discriminated between low‐infestation and high‐infestation fields in 95% of cases.

Adolescent to young adult longitudinal development of subcortical volumes in two European sites with four waves.

Adolescent subcortical structural brain development might underlie psychopathological symptoms, which often emerge in adolescence. At the same time, sex differences exist in psychopathology, which might be mirrored in underlying sex differences in structural development. However, previous studies showed inconsistencies in subcortical trajectories and potential sex differences. Therefore, we aimed to investigate the subcortical structural trajectories and their sex differences across adolescence using for the first time a single cohort design, the same quality control procedure, software, and a general additive mixed modeling approach. We investigated two large European sites from ages 14 to 24 with 503 participants and 1408 total scans from France and Germany as part of the IMAGEN project including four waves of data acquisition. We found significantly larger volumes in males versus females in both sites and across all seven subcortical regions. Sex differences in age-related trajectories were observed across all regions in both sites. Our findings provide further evidence of sex differences in longitudinal adolescent brain development of subcortical regions and thus might eventually support the relationship of underlying brain development and different adolescent psychopathology in boys and girls.

A scalar-on-quantile-function approach for estimating short-term health effects of environmental exposures.

Environmental epidemiologic studies routinely utilize aggregate health outcomes to estimate effects of short-term (eg, daily) exposures that are available at increasingly fine spatial resolutions. However, areal averages are typically used to derive population-level exposure, which cannot capture the spatial variation and individual heterogeneity in exposures that may occur within the spatial and temporal unit of interest (eg, within a day or ZIP code). We propose a general modeling approach to incorporate within-unit exposure heterogeneity in health analyses via exposure quantile functions. Furthermore, by viewing the exposure quantile function as a functional covariate, our approach provides additional flexibility in characterizing associations at different quantile levels. We apply the proposed approach to an analysis of air pollution and emergency department (ED) visits in Atlanta over 4 years. The analysis utilizes daily ZIP code-level distributions of personal exposures to 4 traffic-related ambient air pollutants simulated from the Stochastic Human Exposure and Dose Simulator. Our analyses find that effects of carbon monoxide on respiratory and cardiovascular disease ED visits are more pronounced with changes in lower quantiles of the population's exposure. Software for implement is provided in the R package nbRegQF.

Association between cigar use, with and without cigarettes, and incident diagnosed COPD: a longitudinal cohort study

BackgroundWhile regular cigar smoking is believed to carry similar health risks as regular cigarette smoking, the impact of cigar use, alone or in combination with cigarettes, on obstructive pulmonary disease (COPD) has not been well characterized. The purpose of this study was to examine the prospective association between exclusive and dual cigar and cigarette use and incident self-reported diagnosed COPD.MethodsThis study used data from Waves 1–5 (2013–2019) of the Population Assessment of Tobacco and Health (PATH) Study, a nationally representative survey of U.S. adults. Longitudinal data from adults aged 40 to 79 at Wave 1, without a pre-existing COPD diagnosis who participated at follow-up interview were analyzed. A time-varying current tobacco exposure, lagged by one wave and categorized as: (a) never/non-current use; (b) exclusive cigar use; (c) exclusive cigarette use; and (d) dual cigar/cigarette use. Multivariable models adjusted for demographics (age, sex, race or ethnicity, education), clinical risk factors (asthma, obesity), and smoking-related confounders (second-hand smoke exposure, other combustible tobacco product use, e-cigarette use, time since quitting, cigarette pack-years). The incidence of self-reported diagnosed COPD was estimated using discrete-time survival models, using a general linear modeling (GLM) approach with a binomial distribution and a complementary log-log link function.ResultsThe analytic sample consisted of 9,556 adults with a mean (SD) age of 56 (10.4), who were predominately female (52.8%) and Non-Hispanic White (70.8%). A total of 906 respondents reported a diagnosis of COPD at follow-up. In the fully adjusted model, exclusive cigar use (adjusted hazard ratio (aHR) = 1.57, 95% CI: 0.77, 3.21) was not associated with increased COPD risk compared to non-use, while exclusive cigarette use (aHR = 1.48, 95% CI: 1.13, 1.93) and dual cigar/cigarette use (aHR = 1.88, 95% CI: 1.24, 2.85) were.ConclusionsExclusive cigarette use and dual cigar/cigarette use were associated with diagnosed incident COPD. These results suggest that cigars, when used in combination with cigarettes, may be associated with poorer COPD health outcomes. Dual use may promote a higher likelihood of inhaling cigar smoke, and future research would benefit from examining whether inhalation of cigar smoke increases COPD risk.