Comparison of Methods of Eliciting Vital Capacity: Forced Versus Slow Vital Capacity.

Background: Methods to elicit the vital capacity (VC) include forced vital capacity (FVC) and slow vital capacity (SVC). Because the FVC maneuver can be affected by air trapping or inefficiencies in lung emptying vs. the SVC, the SVC-FVC difference may be substantial and diagnostically meaningful in elderly individuals and patients with respiratory obstruction.

A criterion for sequential Cohen-Macaulayness.

The purpose of this note is to show that a finitely generated graded module over , a field, is sequentially Cohen-Macaulay if and only if its arithmetic degree agrees with , where is a graded free -module and . This answers positively a conjecture of Lu and Yu from 2016.

Smartphone Recordings are Comparable to "Gold Standard" Recordings for Acoustic Measurements of Voice.

Purpose: The purpose of this study was to assess the relationship and comparability of cepstral and spectral measures of voice obtained from a high-cost "flat" microphone and precision sound level meter (SLM) vs. high-end and entry level models of commonly and currently used smartphones (iPhone i12 and iSE; Samsung s21 and s9 smartphones). Device comparisons were also conducted in different settings (sound-treated booth vs.

Numerical analysis of unsteady momentum and heat flow of dusty tangent hyperbolic fluid in three dimensions.

This paper explores the impact of MHD and viscous dissipation with joule heating on convective stretching flow of dusty tangent hyperbolic fluid over a sheet in 3D. A time-dependent magnetic field is applied along the z-axis and the sheet being stretched along the xy-plane. The fluid and dust particles motions are coupled only through drag and heat transfer between them.

Model-assisted deep learning of rare extreme events from partial observations.

To predict rare extreme events using deep neural networks, one encounters the so-called small data problem because even long-term observations often contain few extreme events. Here, we investigate a model-assisted framework where the training data are obtained from numerical simulations, as opposed to observations, with adequate samples from extreme events. However, to ensure the trained networks are applicable in practice, the training is not performed on the full simulation data; instead, we only use a small subset of observable quantities, which can be measured in practice.

Modeling the population impacts of avian malaria on Hawaiian honeycreepers: Bifurcation analysis and implications for conservation.

Avian malaria is a mosquito-borne parasitic disease of birds caused by protists of the genera Plasmodium, most notably Plasmodium relictum. This disease has been identified as a primary cause of the drastic decline and extinctions of birds, in particular Hawaiian honeycreepers (Drepanidinae), where rates of mortality may exceed 90%. We formulate an epizootiological model of the transmission dynamics of avian malaria between populations of bird hosts and mosquito vectors using a system of compartmental ordinary differential equations.

Associations among osteocalcin, leptin and metabolic health in children ages 9-13 years in the United States.

Background: This study aimed to investigate the relationships among osteocalcin, leptin and metabolic health outcomes in children ages 9-13 years.

Methods: This was a cross-sectional analysis of baseline data from 161 boys and 157 girls (ages 9-13 years) who previously participated in a double-blinded randomized placebo controlled trial of vitamin D supplementation. Relationships among fasting serum total osteocalcin (tOC), undercarboxylated osteocalcin (ucOC), leptin, and metabolic health outcomes were analyzed.

COMPUTATION OF ℛ IN AGE-STRUCTURED EPIDEMIOLOGICAL MODELS WITH MATERNAL AND TEMPORARY IMMUNITY.

For infectious diseases such as pertussis, susceptibility is determined by immunity, which is chronological age-dependent. We consider an age-structured epidemiological model that accounts for both passively acquired maternal antibodies that decay and active immunity that wanes, permitting reinfection. The model is a 6-dimensional system of partial differential equations (PDE).

An age-structured model for the coupled dynamics of HIV and HSV-2.

Evidence suggests a strong correlation between the prevalence of HSV-2 (genital herpes) and the perseverance of the HIV epidemic. HSV-2 is an incurable viral infection, characterized by periodic reactivation. We construct a model of the co-infection dynamics between the two diseases by incorporating a time-since-infection variable to track the alternating periods of infectiousness of HSV-2.

A model for the coupled disease dynamics of HIV and HSV-2 with mixing among and between genders.

Evidence indicates that those with genital herpes (HSV-2) infections have greater risks of infection by HIV; and, once co-infected, are more likely to transmit HIV. To better understand the interactions between HIV and HSV-2, we construct a mathematical model that describes the joint dynamics. A new feature of this model is the inclusion of both heterosexual and homosexual interactions.

A double age-structured model of the co-infection of tuberculosis and HIV.

After decades on the decline, it is believed that the emergence of HIV is responsible for an increase in the tuberculosis prevalence. The leading infectious disease in the world, tuberculosis is also the leading cause of death among HIV-positive individuals. Each disease progresses through several stages.

Extending the limits of quantitative proteome profiling with data-independent acquisition and application to acetaminophen-treated three-dimensional liver microtissues.

The data-independent acquisition (DIA) approach has recently been introduced as a novel mass spectrometric method that promises to combine the high content aspect of shotgun proteomics with the reproducibility and precision of selected reaction monitoring. Here, we evaluate, whether SWATH-MS type DIA effectively translates into a better protein profiling as compared with the established shotgun proteomics. We implemented a novel DIA method on the widely used Orbitrap platform and used retention-time-normalized (iRT) spectral libraries for targeted data extraction using Spectronaut.

Recent developments of analysis for hydrodynamic flow of nematic liquid crystals.

The study of hydrodynamics of liquid crystals leads to many fascinating mathematical problems, which has prompted various interesting works recently. This article reviews the static Oseen-Frank theory and surveys some recent progress on the existence, regularity, uniqueness and large time asymptotic of the hydrodynamic flow of nematic liquid crystals. We will also propose a few interesting questions for future investigations.

Experimental design for dynamics identification of cellular processes.

We address the problem of using nonlinear models to design experiments to characterize the dynamics of cellular processes by using the approach of the Maximally Informative Next Experiment (MINE), which was introduced in W. Dong et al. (PLoS ONE 3(8):e3105, 2008) and independently in M.

A probit latent class model with general correlation structures for evaluating accuracy of diagnostic tests.

Traditional latent class modeling has been widely applied to assess the accuracy of dichotomous diagnostic tests. These models, however, assume that the tests are independent conditional on the true disease status, which is rarely valid in practice. Alternative models using probit analysis have been proposed to incorporate dependence among tests, but these models consider restricted correlation structures.

Meta-analysis combines affymetrix microarray results across laboratories.

With microarray technology becoming more prevalent in recent years, it is now common for several laboratories to employ the same microarray technology to identify differentially expressed genes that are related to the same phenomenon in the same species. Although experimental specifics may be similar, each laboratory will typically produce a slightly different list of statistically significant genes, which calls into question the validity of each gene list (i.e.

Effective labeling of molecular surface points for cavity detection and location of putative binding sites.

We present a method for detecting and comparing cavities on protein surfaces that is useful for protein binding site recognition. The method is based on a representation of the protein structures by a collection of spin-images and their associated spin-image profiles. Results of the cavity detection procedure are presented for a large set of non-redundant proteins and compared with SURFNET-ConSurf.

Metric learning for text documents.

Many algorithms in machine learning rely on being given a good distance metric over the input space. Rather than using a default metric such as the Euclidean metric, it is desirable to obtain a metric based on the provided data. We consider the problem of learning a Riemannian metric associated with a given differentiable manifold and a set of points.

Bayesian models and Markov chain Monte Carlo methods for protein motifs with the secondary characteristics.

Statistical methods have been developed for finding local patterns, also called motifs, in multiple protein sequences. The aligned segments may imply functional or structural core regions. However, the existing methods often have difficulties in aligning multiple proteins when sequence residue identities are low (e.

Adjusted Kaplan-Meier estimator and log-rank test with inverse probability of treatment weighting for survival data.

Estimation and group comparison of survival curves are two very common issues in survival analysis. In practice, the Kaplan-Meier estimates of survival functions may be biased due to unbalanced distribution of confounders. Here we develop an adjusted Kaplan-Meier estimator (AKME) to reduce confounding effects using inverse probability of treatment weighting (IPTW).