Measurement Of Information Research Articles

Cardiac sound classification using a hybrid approach: MFCC-based feature fusion and CNN deep features

The detection of cardiovascular diseases through the analysis of phonocardiograms (PCGs), which are digital recordings of heartbeat sounds, is crucial for early diagnosis. Conventional feature extraction methods often face challenges in distinguishing non-stationary signals like healthy and pathological PCG signals. Our research addresses these challenges by adopting a hybrid feature extraction scheme that leverages deep learning and handcrafted techniques. This approach allows for a more effective analysis and classification of PCG signals. This paper presents a novel approach to PCG signal classification, leveraging a fusion of deep learning features and handcrafted features based on mutual information measurements. High-level features are obtained through a pretrained deep network applied to time-frequency representations of PCG signals. Additionally, Mel-Frequency Cepstral Coefficients of empirical wavelet subbands serve as handcrafted features. Canonical correlation analysis is employed for feature fusion, effectively combining crucial information from both feature types. Classification is performed using support vector machines, k-nearest neighbor, and multilayer perceptron (MLP) classifiers with a fivefold cross-validation approach. Evaluation using the Physionet Challenge 2016 database demonstrates the superior performance of our proposed approach compared to existing state-of-the-art studies, showcasing its efficacy in PCG signal classification.

Growth and Survival of a Cohort of Congenital Zika Virus Syndrome Children Born With Microcephaly and Children Who Developed With Microcephaly After Birth.

Little is known about the clinical course of children born with congenital Zika virus syndrome (CZS). This article aimed to analyze the growth and survival of children with CZS born with microcephaly and children who developed with microcephaly after birth in the 36-month period. This is a cohort of children diagnosed with CZS who were monitored in a series of outpatient appointments, with clinical and demographic information and anthropometric measurements collected. The Mann-Kendall test evaluated the trend of the mean Z-score of head circumference (HC) for age and the Kaplan-Meier model described the time to low weight and short length according to the classification of HC at birth. Children born without microcephaly had a reduction in HC growth velocity (P = 0.019) and took longer to reach low weight (P = 0.036) and short length (P = 0.034) when compared with those born with microcephaly. Seven (10%) deaths were reported, and the probability of survival after 36 months of age was 88%. In children with arthrogryposis, the risk of death was 7 times as high as in those without this condition (adjusted hazard ratio: 6.49; 95% confidence interval: 1.31-32.20; P = 0.022). In this cohort of children with CZS, 20% were born without microcephaly and all of them presented a reduction in HC growth velocity, which led to microcephaly. Progression to low weight and short length occurred in the first years of life, and that was faster in those born with microcephaly. Healthcare providers should be aware of these conditions that pose a risk of unfavorable anthropometric measurements and death.

Estimating the Benefit of Transplant Over Dialysis in Candidates Over 55 Years.

'Life Years from Transplant' (LYFT) is a measure of the predicted difference between the expected lifespan with and without a kidney transplant. The metric was originally proposed in 1999; since then, demographics of the kidney transplant candidate population have materially changed. Using contemporary SRTR data, we propose more sophisticated methods for estimating LYFT with a focus on older kidney transplant candidates, a growing sector of the current candidate pool. We examine trends in predicted LYFT from 1995 to 2020. We show that among older patients on the deceased donor waitlist, transplant remains a better option compared with dialysis (overall LYFT=5 years). LYFT trends have diminished modestly (by <1 life year) over time, in part related to efforts to enhance access to transplantation through intercurrent policy changes. Updated LYFT estimates remain informative clinical measures that can support patient-centered decision making. However less homogenous metrics with meaningful disaggregation are needed to inform institutional evaluation and policy change. Models should be repeatedly evaluated as demographics of the candidate pool evolve.

Generative approach for lensless imaging in low-light conditions.

Lensless imaging offers a lightweight, compact alternative to traditional lens-based systems, ideal for exploration in space-constrained environments. However, the absence of a focusing lens and limited lighting in such environments often results in low-light conditions, where the measurements suffer from complex noise interference due to insufficient capture of photons. This study presents a robust reconstruction method for high-quality imaging in low-light scenarios, employing two complementary perspectives: model-driven and data-driven. First, we apply a physics-model-driven perspective to reconstruct the range space of the pseudo-inverse of the measurement model-as a first guidance to extract information in the noisy measurements. Then, we integrate a generative-model-based perspective to suppress residual noises-as the second guidance to suppress noises in the initial noisy results. Specifically, a learnable Wiener filter-based module generates an initial, noisy reconstruction. Then, for fast and, more importantly, stable generation of the clear image from the noisy version, we implement a modified conditional generative diffusion module. This module converts the raw image into the latent wavelet domain for efficiency and uses modified bidirectional training processes for stabilization. Simulations and real-world experiments demonstrate substantial improvements in overall visual quality, advancing lensless imaging in challenging low-light environments.

Fractional tackles: leveraging player tracking data for within-play tackling evaluation in American football

Tackling is a fundamental defensive move in American football, with the main purpose of stopping the forward motion of the ball-carrier. However, current tackling metrics are manually recorded outcomes that are inherently flawed due to their discrete and subjective nature. Using player tracking data, we present a novel framework for assessing tackling contribution in a continuous and objective manner. Our approach first identifies when a defender is in a “contact window” of the ball-carrier during a play, before assigning value to each window and the players involved. This enables us to devise a new metric called fractional tackles, which credits defenders for halting the ball-carrier’s forward motion toward the end zone. We demonstrate that fractional tackles overcome the shortcomings of traditional metrics such as tackles and assists, by providing greater variation and measurable information for players lacking recorded statistics like defensive linemen. We view our contribution as a significant step forward in measuring defensive performance in American football and a clear demonstration of the capabilities of player tracking data.

Regulatory responses to ultra-processed foods are skewed towards behaviour change and not food system transformation.

Growing evidence suggests that diets high in ultra-processed foods (UPFs) are harming human and planetary health. UPFs therefore pose a complex regulatory challenge, yet, to date, little research has systematically assessed how governments have responded to UPFs in national food policies. Here we analyse data from the NOURISHING database to assess the scope and strength of UPF-related regulatory interventions worldwide, using three frameworks-namely, NOURISHING, the Nuffield Ladder and the Modalities of Control framework. Of the 417 UPF-related measures identified, most imply food processing or mention UPF examples rather than refer to processing or UPFs specifically. The scope of action is narrow; 85.9% of interventions change the food environment, largely represented by nutrition labelling. The strength of action is limited; interventions are skewed towards informational measures to influence consumer choice, and 47.1% of measures use consensus to shape food business conduct. These findings highlight an opportunity to broaden the scope and strength of UPF-related regulation.

Three-dimensional measurement of the depth of invasion in oral squamous cell carcinoma samples using Lugol's iodine-enhanced micro-computed tomography: an original study.

Depth of invasion (DOI) in oral squamous cell carcinoma (OSCC) guides treatment and prognosis but lacks three-dimensional (3D) insight. Thus, this study aimed to investigate the feasibility and accuracy of Lugol's iodine-enhanced micro-computed tomography (CT) for the 3D measurement of DOI in OSCC samples. In total, 50 in vitro OSCC samples from Nanjing Stomatological Hospital (July 2022 to January 2024) were subjected to micro-CT imaging with a slice thickness of 50 μm following 3% Lugol iodine staining for 12 h, followed by pathological examination and staining. The panoramic diagnostic scanner digitally measured pathological DOI. The micro-CT DOI was measured by evaluating the voxel value of the boundary of the tumor lesion and comparing it with the pathological examination results. Experienced physicians analyzed both measurements, and statistical analyses were performed to determine their correlation. Lugol iodine-enhanced micro-CT imaging distinguishes various tissue structures, such as tumor tissue, epithelial tissue, muscle tissue, blood vessel structure, and other major tissue structures in 3D space. This imaging technique found and localized micro-tumor lesions (1.82×1.5×1 mm3) when in conjunction with pathological sections. Statistical analysis indicated a strong correlation between pathological DOI and micro-CT DOI (P<.001; r=0.986). During DOI measurement, Lugol iodine-enhanced micro-CT imaging effectively compensated for the loss of 3D space information in the pathological measurements, improving the accuracy of the DOI measurement. Lugol iodine-enhanced micro-CT improves OSCC DOI 3D measurements, enhances pathological staging accuracy, and aids treatment decisions and prognosis.

Assessment of Frost Depth in Romania

The study of severe climate and weather conditions has accelerated in recent decades, partly due to political engagement. However, historical climate monitoring data has not received sufficient attention. Reliable assessments of the maximum extent of soil freezing are crucial for determining construction costs and building foundations. Structural designers also require reliable local meteorological data. This study presents calculations of these parameters for Cluj Napoca city. For instance, a revised frost depth map for Romania is necessary due to recent climate studies indicating a rise in both regional and global surface temperatures, with the most notable warming for the previous thirty years. The findings from this investigation could help reduce frost-related disasters and inform policies and measures for adapting geotechnical and structural designs in Romania.

The relationship between temperament with nutritional status and anthropometric measurements in adult individuals.

Interest in studies examining the effect of temperament types on nutrition has recently increased. The aim of this study was to evaluate the relationship between nine types of temperament, anthropometric measurements, and nutrition in adults. This study was conducted on 1317 individuals aged between 18 and 55 years. Descriptive information, dietary habits and anthropometric measurements of the participants were questioned. The Nine Types of Temperament Scale was administered to the individuals and food consumption records were obtained with a 24-hour retrospective reminder method. Type 2 scores of obese participants were higher than those of underweight and normal body weight; Type 8 scores of overweight participants were higher than those of normal body weight. Daily dietary intake of protein, riboflavin, folate, vitamins K, C, calcium, iron, and cholesterol were negatively associated with Type 1 score; protein, magnesium, iron, zinc intake, and water consumption were negatively associated with Type 2 score. Type 3 score was negatively associated with dietary CHO (%), dietary magnesium, iron, and zinc intake and positively associated with water consumption. The results of the study indicate significant relationships between temperament types, dietary habits, and anthropometric measures. In this context, considering temperament types when planning dietary patterns of individuals may be a new approach.

Recent Advances in Tunable External Cavity Diode Lasers

A narrow linewidth tunable laser source is a critical component in various fields, including laser radar, quantum information, coherent communication, and precise measurement. Tunable external cavity diode lasers (ECDLs) demonstrate excellent performance, such as narrow linewidth, wide tunable range, and low threshold current, making them increasingly versatile and widely applicable. This article provides an overview of the fundamental structures and recent advancements in external cavity semiconductor lasers. In particular, we discuss external cavity semiconductor lasers based on quantum well and quantum dot gain chips. The structure of the gain chip significantly influences laser’s performance. External cavity quantum well laser has a narrower linewidth, higher power, and better mode stability. Conversely, external cavity quantum dot laser provides a wider tunable range and a remarkably lower threshold current. Furthermore, dual-wavelength external cavity tunable diode lasers are gaining importance in applications such as optical switching and terahertz radiation generation. With the continuous optimization of chips and external cavity structures, external cavity diode lasers are increasingly recognized as promising light sources with narrow linewidth and wide tunability, opening up broader application prospects.

A Novel Filtering Based Maximum Likelihood Generalized Extended Gradient Method for Multivariable Nonlinear Systems

ABSTRACTThis study proposes a filtering based maximum likelihood generalized extended gradient algorithm for multivariable nonlinear systems with autoregressive moving average noises. The parameter estimates are obtained by minimizing the half squared residual measurement which can approach the true values. An auxiliary model is also established with the measurable information of the system, and the output of the auxiliary model is used to replace the unmeasurable variables of the system, so that the output of the auxiliary model approximates these unmeasurable variables, so as to obtain the consistent estimation of the system parameters. A maximum likelihood generalized extended gradient algorithm is derived for comparison and a numerical example is provided to show the effectiveness of the proposed method and the estimates converge to the actual values quickly.

Mitigating unintentional injury deaths in sport and recreation: insights from 14 years of coroner recommendations in Québec, Canada.

Unintentional injury deaths in sport and recreation represent a significant public health concern. This study analysed coronial recommendations related to such deaths, focusing on case specifics and recurring themes from January 2006 to December 2019. This mixed-methods study used data from the Bureau du coroner du Québec. Reports with recommendations were analysed by sex, age group, context, mechanism and activity. A four-phase thematic analysis was conducted to emphasise the developed themes and connect them with the existing literature. Of 1937 coronial reports reviewed, 13.3% (n=258) contained at least one recommendation, totalling 609 recommendations (31 per 100 activity-related deaths). Reports were more likely to contain at least one recommendation for women (20.3%, p=0.0004), paediatric populations (≤5 years: 30.3%, p<0.0001; 6-11 years: 29.3%, p=0.0003; 12-17 years: 27.6%, p<0.0001), and organised events (55.0%, p<0.0001), despite most deaths occurring among men, adults and during unstructured events. All-terrain vehicle and snowmobile activities showed significantly lower rates of reports with recommendations (8.1%, p=0.0008 and 8.6%, p=0.0044, respectively). Most frequently addressed themes were Development, inspection and modification of bicycle infrastructure for cycling and Lake and river safety measures for swimming. Conflict with other types of users was the top theme for land motorsports, while Personal flotation device use was the most common for navigation activities. Patterns from reports with recommendations will be shared with the Bureau du Coroner du Québec to improve coronial practices. Integrating recurrent themes and recommendations with activity-specific risk factors will help identify critical patterns and inform preventive measures holistically.

Joint-measurability and quantum communication with untrusted devices

Photon loss represents a major challenge for the implementation of quantum communication protocols with untrusted devices, e.g. in the device-independent (DI) or semi-DI approaches. Determining critical loss thresholds is usually done in case-by-case studies. In the present work, we develop a general framework for characterizing the admissible levels of loss and noise in a wide range of scenarios and protocols with untrusted measurement devices. In particular, we present general bounds that apply to prepare-and-measure protocols for the semi-DI approach, as well as to Bell tests for DI protocols. A key step in our work is to establish a general connection between quantum protocols with untrusted measurement devices and the fundamental notions of channel extendibility and joint-measurability, which capture essential aspects of the communication and measurement of quantum information. In particular, this leads us to introduce the notion of partial joint-measurability, which naturally arises within quantum cryptography.

Informeasure: an R/bioconductor package for quantifying nonlinear dependence between variables in biological networks from an information theory perspective

BackgroundUsing information measures to infer biological regulatory networks can capture nonlinear relationships between variables. However, it is computationally challenging, and there is a lack of convenient tools.ResultsWe introduce Informeasure, an R package designed to quantify nonlinear dependencies in biological regulatory networks from an information theory perspective. This package compiles a comprehensive set of information measurements, including mutual information, conditional mutual information, interaction information, partial information decomposition, and part mutual information. Mutual information is used for bivariate network inference, while the other four estimators are dedicated to trivariate network analysis.ConclusionsInformeasure is a turnkey solution, allowing users to utilize these information measures immediately upon installation. Informeasure is available as an R/Bioconductor package at https://bioconductor.org/packages/Informeasure.

Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders

Coherent diffraction imaging (CDI) is an advanced non-destructive 3D X-ray imaging technique for measuring a sample’s electron density. The main challenge of CDI is loss of phase information in diffraction intensity measurements, resulting in lengthy iterative reconstruction processes that can return non-unique solutions, which pose challenges for experiments attempting to track dynamic sample evolution through multiple states. As the increased brightness of fourth-generation light sources enables faster sample measurements and drives operando experiments with Bragg CDI, there is a growing need for faster reconstruction techniques that can keep pace. We have developed an adaptive generative autoencoder approach for uniquely tracking a sample’s electron density as it dynamically evolves. Our approach adaptively tunes the low-dimensional latent embedding of a generative autoencoder, enabling a computationally efficient manner to account for time-varying shifting distributions in real-time. Analytic proof of convergence is provided as well as numerical demonstration of sample tracking with noisy measurements.

An Observational Study on the Prediction of Range of Motion in Soldiers Diagnosed with Patellar Tendinopathy Using Ultrasound Shear Wave Elastography.

This study hypothesized that changes in the elasticity of the quadriceps and patellar tendons before and after the diagnosis of patellar tendinopathy would correlate with the range of motion (ROM) following conservative treatment. We aimed to prospectively assess post-treatment ROM using multinomial logistic regression, incorporating elasticity measurements obtained via shear wave elastography (SWE). From March 2023 to April 2024, 95 patients (86 men; aged 20-45 years, mean 25.62 ± 5.49 years) underwent SWE preoperatively and two days post-diagnosis of patellar tendinopathy. Elasticity measurements of the rectus femoris, vastus medialis, vastus lateralis, patellar tendon, and biceps tendon were obtained during full flexion and extension. Based on ROM 56 days post-treatment, patients were categorized into two groups: Group A (ROM > 120 degrees) and Group B (ROM < 120 degrees). A multinomial logistic regression algorithm was employed to classify the groups using patient information and tendon elasticity measurements both at diagnosis and 1-week post-diagnosis. The predictive accuracy using only patient information was 62%, while using only elasticity measurements yielded 68% accuracy. When combining patient information with elasticity measurements taken at diagnosis and two days post-diagnosis, the algorithm achieved an accuracy of 79%, sensitivity of 92%, and specificity of 56%. The combination of patient information and tendon elasticity measurements obtained via SWE at pre-conservative treatment and early post-conservative treatment periods effectively predicts post-treatment ROM. This algorithm can guide rehabilitation strategies for soldiers with patellar tendinopathy.

Visible light full Stokes polarization imaging based on twisted liquid crystal micro-polarizer arrays

The micro-polarizer array is the key component of the division of focal-plane (DoFP) polarization imaging method. Currently, it is possible to achieve full Stokes information detection at a single wavelength using a designed array with the highest signal-to-noise ratio. To broaden the working wavelength to the visible range and achieve high-accuracy full Stokes polarization information, this paper proposes a micro-polarizer array structure based on twisted liquid crystal. The particle swarm optimization algorithm is utilized to optimize the device parameters, with the condition number as the evaluation function. A series of elliptically polarized lights are under measurement using the designed device. The results show that the errors of the degree of linear polarization (DoLP), degree of circular polarization (DoCP), and angle of polarization, are less than 2.00%, 1.50%, and 1.45%, respectively. All the results indicate that the twisted liquid crystal micro-polarizer array enables the high-accuracy measurement of full Stokes information within the visible range.

Prediction of low birth weight from fetal ultrasound and clinical characteristics: a comparative study between a low- and middle-income and a high-income country

IntroductionAdverse perinatal outcomes (APO) pose a significant global challenge, particularly in low- and middle-income countries (LMICs). This study aims to analyse two cohorts of high-risk pregnant women for APO to...

Associations between the Dietary Inflammatory Index and fractional exhaled nitric oxide among United States adults: A cross-sectional study.

Fractional exhaled nitric oxide (FeNo) is a convenient and noninvasive test that measures the concentration of nitric oxide in exhalation as a surrogate biomarker of airway inflammation. This cross-sectional study aimed to determine the associations between Dietary Inflammatory Index (DII) and FeNo in US adults. Adults participating in the 2007-2012 cycles of the US National Health and Nutrition Examination Survey with complete information and available measurement data of DII and FeNo were included. Associations between DII and FeNo were assessed using univariable and multivariable logistic regression models, restricted cubic spline analysis, stratified analysis, and sensitivity analysis. A total of 7677 participants (mean age 45.68 years, 53.03% men) with a mean DII of 1.28 and FeNo of 17.33 ppb were included. The multivariable-adjusted linear regression analysis showed that a one-unit increase in DII was associated with a 0.283-ppb reduction in FeNo level. The beta and 95% CI for the second, third, and fourth DII quartile groups were -1.19 (-2.04 to -0.35), -1.07 (-2.26 to 0.12), and -1.60 (-2.85 to -0.36), respectively (P for trend = 0.04), with the lowest quartile group as the reference. The restricted cubic spline curve showed an inversely linear relationship between DII and FeNo. The study result is robust and did not appear to be affected by the participant's age, sex, race, body mass index, physical activity, diabetes status, or white blood cell or eosinophil counts. A proinflammatory diet, as indicated by a higher DII, is cross-sectionally associated with lower FeNo levels in US adults.

Serum vitamin D concentration and anthropometric indicators of adiposity in adults without or with low dose statin users: a cross-sectional study

BackgroundThis study sought to determine the accuracy of several anthropometric parameters in association with serum Vit. D concentrations and to compare the novel indices with the conventional ones.MethodsA total of 947 individuals referred to the cardiology clinic who have not used statin or take low-dose statin were evaluated through a cross-sectional study. Data on demographic information, anthropometric indices, and biochemical measurements were gathered using a checklist. Both the multivariable regression modeling and the area under the receiver-operating characteristic (ROC) were employed for the analysis.ResultsConsidering novel indices, BRI (Body Roundness Index) showed the most powerful correlation with serum Vit. D levels among both genders. Among conventional ancient indices, WC (Waist Circumference) had the strongest association in both men and women groups. Based on the confounding factors-adjusted model, the highest odds ratio (OR) for the presence of Vit. D deficiency belonged to WHtR (Waist to Height Ratio) in women (OR, 0.347 (0.171–0.704), P = 0.003). None of the indices predicted Vit. D deficiency significantly among men. A Vit. D concentration of 4.55 ng/ml was found as a cutoff based on the metabolic syndrome status.ConclusionThe most powerful association with serum Vit. D levels were detected for BRI in both genders among newly developed indices. In addition, WHtR predicted Vit. D deficiency independent of confounding factors among women.