bluuebunny/crossref_metadata_2025_split huggingface dataset:
An introduction to event history analyses for ecologists
Authors: Landes Julie , Engelhardt Sacha C. , Pelletier Fanie 
Published: October 2020

AbstractEfforts to understand the emergence of an event require our ability to measure and understand the dynamics between time in a state (e.g., being alive or a behavior) and the outcome of the state. Studying the main drivers that affect changes in state over time allows researchers to better understand population dynamics and evolutionary processes. Event history analyses provide a range of theoretical and empirical tools to explore the emergence of an event. Their use is still restricted in ecology; however, they are commonly used in human demography. Event history analysis is a powerful tool for measuring the probability that an event occurs at timet. Here, we provide an introductory guide for ecologists who are interested in exploring event history analyses in their research. In the first part of this article, we outline key concepts in event history analyses and present a decision tree, statistical techniques, and their applications to ecological questions. To introduce practical applications of event history analyses, we provide four detailed tutorials, stemming from observational and longitudinal records of events in mammalian and avian species, along with relevant R scripts. We then explain how to interpret and present results of such analyses. Our results show that event history analyses are useful to quantify the effect of factors on the emergence of events. We conclude by highlighting additional strengths, pitfalls, and limitations researchers should be aware of when using such methods. We foresee the use of event history analyses for ecological studies.
Angiotensin‐converting enzyme inhibitor/angiotensin II receptor blocker treatment and haemodynamic factors are associated with increased cardiac mRNA expression of angiotensin‐converting enzyme 2 in patients with cardiovascular disease
Authors: Lebek Simon , Tafelmeier Maria , Messmann Rebecca , Provaznik Zdenek , Schmid Christof , Maier Lars S. , Birner Christoph , Arzt Michael , Wagner Stefan 
Published: October 2020

AbstractAimsCoronavirus disease 2019 (COVID‐19) is a widespread pandemic with an increased morbidity and mortality, especially for patients with cardiovascular diseases. Angiotensin‐converting enzyme 2 (ACE2) has been identified as necessary cell entry point for SARS‐CoV‐2. Previous animal studies have demonstrated an increased ACE2 expression following treatment with either angiotensin‐converting enzyme inhibitors (ACEi) or angiotensin II receptor blockers (ARB) that have led to a massive precariousness regarding the optimal cardiovascular therapy during this pandemic.Methods and resultsWe have measured ACE2 mRNA expression using real‐time quantitative polymerase chain reaction in atrial biopsies of 81 patients undergoing coronary artery bypass grafting and we compared 62 patients that received ACEi/ARB vs. 19 patients that were not ACEi/ARB‐treated. We found atrial ACE2 mRNA expression to be significantly increased in patients treated with an ACEi or an ARB, independent of potential confounding comorbidities. Interestingly, the cardiac ACE2 mRNA expression correlated significantly with the expression in white blood cells of 22 patients encouraging further evaluation if the latter may be used as a surrogate for the former. Similarly, analysis of 18 ventricular biopsies revealed a significant and independent increase in ACE2 mRNA expression in patients with end‐stage heart failure that were treated with ACEi/ARB. On the other hand, cardiac unloading with a left ventricular assist device significantly reduced ventricular ACE2 mRNA expression.ConclusionTreatment with ACEi/ARB is independently associated with an increased myocardial ACE2 mRNA expression in patients with coronary artery disease and in patients with end‐stage heart failure. Further trials are needed to test whether this association is deleterious for patients with COVID‐19, or possibly protective. Nevertheless, haemodynamic factors seem to be equally important for regulation of cardiac ACE2 mRNA expression.
Revisiting smart antenna array design with multiple interferers using basic adaptive beamforming algorithms: Comparative performance study with testbed results
Authors: Imtiaj SK , Misra Iti Saha , Bhattacharya Sandipan 
Published: October 2020

AbstractSmart antennas are becoming popular in the area of cellular wireless communication for capacity enhancement and reduction of the multipath effect and interference. The demand for smart antennas is widely increasing as 5G cellular communication evolves to support the higher data rate and bandwidth. The basic principle of smart antenna design is adaptive beamforming using the best suited digital signal processing algorithms, such as least mean square (LMS), normalized least mean square (NLMS), sample matrix inversion (SMI), and recursive least square (RLS), each having its pros and cons. Among these, the LMS and NLMS are iterative approaches while SMI is a block adaptive method and RLS is a recursive method. The contribution of this article includes easy implementation of four adaptive beamforming algorithms, namely LMS, NLMS, SMI, and RLS. Furthermore, an exhaustive comparative performance analysis is carried out under five interferers and evaluated in terms of beamwidth, null depth, maximum sidelobe level, rate of convergence, error variation for the number of antenna elements, and spacing. Finally, a contrast table is presented to demonstrate the pros and cons of the listed algorithms. Time and dynamic space complexity are studied for RLS and SMI beamforming algorithms. Performance results from a designed reconfigurable testbed model for weight adaptation and smart beamforming are also presented for analysis and a better understanding of the real implementation of the smart algorithms through testbed design. The simulation and testbed results create the ground work for future exploration in the design of smart antenna beamforming.
Modeling of analog battery management system for single cell lithium ion battery
Authors: S Hemavathi 
Published: October 2020

AbstractThe Li‐ion battery is an energy storage system in consumer and industrial applications. Because of their cell and pack level protection, Li‐ion battery requires a battery management system (BMS). The important function of the BMS is to monitor and protect the Li‐ion battery cells and packs from fault conditions, in order to maximize their lifecycle and increase safety features. In this research article, an analog BMS is presented for the protection of nickel manganese cobalt oxide‐chemistry‐based single‐cell Li‐ion battery. The Analog BMS is a battery protection circuit module that includes battery protection integrated circuit to protect batteries from overvoltage, undervoltage, overcurrent charging, and overcurrent discharging conditions. In addition, the semiconductor switches are used for charge and discharge protection control. This protection circuit module is designed for 18650 single‐cell Li‐ion battery and test the performance of analog BMS based on protection parameters. A real‐time experiment is carried out on analog BMS interconnected with 18650 single‐cell Li‐ion battery and tested under different charge and discharge rates using standard constant current‐constant voltage (CC‐CV) charging method. The experimental results show that the developed analog BMS protected single‐cell Li‐ion battery from overvoltage, undervoltage, overcurrent charging, and discharging conditions under different C/5, C/2, and 1C rates.
IOT and context‐aware learning‐based optimal neural network model for real‐time health monitoring
Authors: Kavitha D. , Ravikumar S. 
Published: October 2020

AbstractRecently, numerous context‐aware approaches are established to provide physiological information regarding the wellness and healthcare of each individual. While monitoring the health condition of the patient there occur delays in transferring data to the cloud. So to overcome such types of delays, numerous IoT sensors are developed to monitor, track, and sense the activities of the elder persons. This paper proposes four‐module architecture comprises of IoT module (IoT‐M), data pre‐processing module (DP‐M), context‐aware module (CA‐M) as well as decision‐making module (DM‐M) for storing and processing numerous cumulative sensor data. Here, an IoT comprises a concrete or substantial hardware ecological unit, that is, sensors and actuators. On the other hand, the context‐aware computational approach comprises of insubstantial software ecological unit in understanding and processing the context directly into an accomplishment through various IoT devices. The initial module or the IoT‐M comprises of sensors whereas in the DP‐M phase includes data collection phase, data storage phase, and data redundancy phase. The third phase or the CA‐M comprises two different types of layers namely fog layer, cloud layer. In addition to this, a context‐aware learning phase is also enumerated. In the final phase or the DM‐P phase, the feature extraction and classification is done by Back‐Propagation Neural Network along with the Adaptive grasshopper optimization algorithm so as to obtain a best optimal solution. Thus, an alarm or a notification is sent to the medical practitioner regarding the health condition of the patient with very less response time, high accuracy, and a high scalability rate. The evaluation results and discussions are made by comparing our proposed approach with several other approaches and the evaluation results reveal that the proposed framework provides better results with high accuracy, scalability, network latency, and low response time.
Nutritional characterization of freshwater mud eel (Monopterus cuchia) muscle cooked by different thermal processes
Authors: Islam Md. Aminur , Mohibbullah Md. , Suraiya Sharmin , Sarower‐E‐Mahfuj Md. , Ahmed Shafi , Haq Monjurul 
Published: October 2020

AbstractThis paper reports the effects of four popular cooking methods viz. grilling, boiling, frying, and microwaving on the proximate and nutritional compositions of freshwater mud eel (FWME) muscle. The moisture content of raw FWME muscle was 74.45%, which was similar in boiled products but lower in grilled, fried, and microwaved products (p ≤ .05). The protein content in raw and cooked FWME muscles varied between 14.49% and 21.28%. There were found 20 different fatty acids in FWME muscle of which palmitic acid was the most abundant one with an amount of 26.51%–29.70% in raw and cooked FWME muscles. FWME muscle contained a substantial amount of ω‐3 polyunsaturated fatty acids, ranging from 7.54% to 13.7%. However, the thermal effects during cooking decreased the ω‐3 polyunsaturated fatty acid contents. There were seven essential and eight nonessential amino acids available in FWME muscle; among the essential amino acids, lysine content was the highest. Raw and cooked FWME were very rich in calcium, between 794.52 mg/100 g and 883.24 mg/100 g muscle. Among the studied heavy metals, Pb content was the highest. However, all the heavy metal contents were within acceptable limits determined by health risk assessment, that is, target hazard quotient and target cancer risk.
Nonlinear interaction between APOEε4 allele load and age in the hippocampal surface of cognitively intact individuals
Authors: Martí‐Juan Gerard , Sanroma‐Guell Gerard , Cacciaglia Raffaele , Falcon Carles , Operto Grégory , Molinuevo José Luis , González Ballester Miguel Ángel , Gispert Juan Domingo , Piella Gemma ,   The Alzheimer's Disease Neuroimaging Initiative,   The ALFA Study
Published: October 2020

AbstractThe ε4 allele of the gene Apolipoprotein E is the major genetic risk factor for Alzheimer's Disease. APOE ε4 has been associated with changes in brain structure in cognitively impaired and unimpaired subjects, including atrophy of the hippocampus, which is one of the brain structures that is early affected by AD. In this work we analyzed the impact of APOE ε4 gene dose and its association with age, on hippocampal shape assessed with multivariate surface analysis, in a ε4‐enriched cohort of n = 479 cognitively healthy individuals. Furthermore, we sought to replicate our findings on an independent dataset of n = 969 individuals covering the entire AD spectrum. We segmented the hippocampus of the subjects with a multi‐atlas‐based approach, obtaining high‐dimensional meshes that can be analyzed in a multivariate way. We analyzed the effects of different factors including APOE, sex, and age (in both cohorts) as well as clinical diagnosis on the local 3D hippocampal surface changes. We found specific regions on the hippocampal surface where the effect is modulated by significant APOE ε4 linear and quadratic interactions with age. We compared between APOE and diagnosis effects from both cohorts, finding similarities between APOE ε4 and AD effects on specific regions, and suggesting that age may modulate the effect of APOE ε4 and AD in a similar way.
Role of physician density in predicting stage and survival for head and neck squamous cell carcinoma
Authors: Gadkaree Shekhar K. , McCarty Justin C. , Feng Allen L. , Siu Jennifer M. , Burks Ciersten A. , Deschler Daniel G. , Richmon Jeremy D. , Varvares Mark A. , Bergmark Regan W. 
Published: October 2020

AbstractBackgroundIdentifying and linking barriers to access to head and neck cancer care, specifically provider density, to stage of diagnosis and survival outcomes is important to serve as a foundation for policy interventions.MethodsRetrospective cohort study using patients with head and neck squamous cell (HNSCC) in the Surveillance, Epidemiology, and End Results (SEER) database from 2007 to 2016 and Area Resource File. Primary outcomes included stage of presentation and cancer‐specific 5‐year survival and relation to provider density.ResultsThe initial cohort consisted of 18 342 patients with oral cavity, 21 809 oropharyngeal, 15 860 laryngeal, and 2887 patients with hypopharyngeal malignancy. Non‐Hispanic Black race and being uninsured increased the odds of presenting with advanced stage HNSCC and increased hazard of death. There was no significant and consistent association identified between Health Service Areas provider density and advanced stage at diagnosis or cancer‐specific 5‐year mortality.ConclusionsProvider density of otolaryngologists and primary care physicians and dentists was not significantly associated with stage of presentation or cancer‐specific survival for HNSCC while race and insurance status remained independent predictors for worse outcomes.
Echocardiographic evaluation of left ventricular systolic function by the M‐mode lateral mitral annular plane systolic excursion in patients with Duchenne muscular dystrophy age 0‐21 years
Authors: Webb Melissa K. , Thankavel Poonam P. , Ramaciotti Claudio 
Published: October 2020

AbstractBackground and AimsDuchenne muscular dystrophy (DMD) results in cardiac fibrosis and dysfunction. These patients frequently have poor image quality. Mitral annular plane systolic excursion (MAPSE) is a reproducible and reliable method for determining function and can be a valuable tool in patients with poor images. Our study was performed to evaluate the feasibility of MAPSE and compare it to shortening fraction (SF) in patients with DMD.MethodsLateral M‐mode MAPSE was obtained on all echocardiograms performed on DMD patients aged 0 to 21 years between October 2013 and April 2015. Retrospectively, interobserver and intraobserver variability was determined for these measurements and each measurement was compared to patient characteristics and measured values of SF.ResultsThere was good interobserver (r2 = .66, P = .0081) correlation. Seventeen of 59 echocardiograms (29%) had abnormal SF while 32 (54%) echocardiograms had an abnormal M‐mode lateral MAPSE Z‐score. There was no significant association between lateral MAPSE Z‐score and SF. Age at the time of echocardiogram and time from diagnosis to echocardiogram both had a significant negative correlation with lateral MAPSE.ConclusionsLateral M‐mode MAPSE measurements are reproducible in young patients with Duchenne muscular dystrophy. M‐mode lateral MAPSE may worsen over length of time with Duchenne muscular dystrophy. Further studies are necessary to provide absolute conclusions, but this study shows that lateral M‐mode MAPSE may be a valuable additional tool at routine echocardiogram in these patients.
A wearable carotid Doppler tracks changes in the descending aorta and stroke volume induced by end‐inspiratory and end‐expiratory occlusion: A pilot study
Authors: Kenny Jon‐Émile S. , Barjaktarevic Igor , Eibl Andrew M. , Parrotta Matthew , Long Bradley F. , Eibl Joseph K. 
Published: October 2020

AbstractBackground and AimsTo test the feasibility of a novel, wearable carotid Doppler ultrasound to track changes in cardiac output induced by end‐inspiratory and end‐expiratory occlusion tests.MethodsWe observed the pattern of Doppler change of the common carotid artery during a simulated end‐inspiratory and expiratory occlusion test (sEIOT/sEEOT) in 10, nonventilated, healthy subjects. Simultaneously, we measured the Doppler signal of the descending aorta using duplex ultrasound (Xario, Toshiba Medical Systems) and stroke volume (SV) using noninvasive pulse contour analysis (Clearsight, Edwards Lifesciences, Irvine, California).ResultsDuring sEIOT, SV, maximum velocity time integral (VTI) of the descending aorta, and common carotid fell by 25.7% (P = .0131), 26.1% (P < .0001), and 18.5% (P < .0001), respectively. During sEEOT, SV, maximum VTI of the descending aorta, and common carotid rose by: 41.3% (P = .0051), 28.3% (P < .0001), and 41.6% (P < .0001), respectively. There was good correlation between change in aortic VTI and carotid VTI (r2 = 0.79); SV and aortic VTI (r2 = 0.82), and SV and carotid VTI (r2 = 0.95).The coefficient of variation of the VTI measured by the Doppler patch was roughly 60% less than that of the duplex system.ConclusionsThe pattern of SV change induced by a sEIOT/sEEOT in nonmechanically ventilated volunteers is reflected in the common carotid artery and descending aorta. The VTI variability of the Doppler patch was less than that of the traditional, duplex Doppler.
Detection of pneumonia in chest X‐ray images by using 2D discrete wavelet feature extraction with random forest
Authors: Akgundogdu Abdurrahim 
Published: October 2020

AbstractPneumonia is one of the most common and fatal diseases in the world. Early diagnosis and treatment are important factors in reducing mortality caused by the aforementioned disease. One of the most important and common techniques to diagnose pneumonia disease is the X‐ray images. By evaluating these images, various machine‐learning methods are used for accuracy in diagnosis. The presented study in this article utilizes machine‐learning techniques to evaluate these X‐ray images. The diagnosis of pediatric pneumonia is classified with a proposed machine learning method by using the chest X‐ray images. The proposed system firstly utilizes a two‐dimensional discrete wavelet transform to extract features from images. The features obtained from the wavelet method are labeled as normal and pneumonia and applied to the classifier for classification. Besides, Random Forest algorithm is used for the classification technique of 5856 X‐ray images. A 10‐fold cross‐validation method is used to evaluate the success of the proposed method and to ensure that the system avoided overfitting. By using various machine learning algorithms, simulation results reveal that the Random Forest method is proposed and it gives successful results. Results also show that, at the end of the training and validation process, the proposed method achieves higher success with an accuracy of 97.11%.
Genotoxic effect of simultaneous therapeutic exposure to polycyclic aromatic hydrocarbons and UV radiation
Authors: Malkova Andrea , Borska Lenka , Smejkalova Jindra , Hamakova Kvetoslava , Kremlacek Jan , Svadlakova Tereza , Borsky Pavel , Holmannova Drahomira , Fiala Zdenek 
Published: October 2020

AbstractPolycyclic aromatic hydrocarbons (PAHs) and ultraviolet radiation (UV) represent genotoxic factors that commonly occur in the living and working environment. The dermal form of exposure represents a significant part of the total load of dangerous chemical and physical environmental factors to which an organism is subjected. However, simultaneous dermal exposures to PAHs (pharmaceutical crude coal tar [CCT]) and UV (UVA and UVB) also have therapeutic uses. A typical example is Goeckerman therapy (GT) for psoriasis. The question of the therapeutic efficacy of GT and the related level of genotoxic danger is still under discussion. The aim of the present study was to compare four GT variants (G1–G4) in terms of efficacy and acceptable genotoxic hazard. Efficacy was expressed by the psoriasis area of severity index (PASI) score, genotoxic hazard by chromosomal aberration in peripheral lymphocytes. The lowest risk of genotoxic hazard and the lowest efficiency was observed in G1 variant (3% of the CCT and UVA + UVB). The efficacy of G2 (4% CCT and UVA + UVB), G3 (4% CCT and UVB), and G4 variants (5% CCT and UVA + UVB) was comparable. The highest risk of genotoxic hazard was found in the G3 variant. In the terms of sufficient efficacy and acceptable genotoxic hazard, a combination of 4% or 5% of CCT and UVA and UVB seems to be acceptable (variants G2 and G4).
Toxicokinetics of methylmercury in diabetic KK‐Ay mice and C57BL/6 mice
Authors: Yamamoto Megumi , Yanagisawa Rie , Sakai Atsushi , Mogi Masaki , Shuto Satoshi , Shudo Masachika , Kashiwagi Hazuki , Kudo Megumi , Nakamura Masaaki , Sakamoto Mineshi 
Published: October 2020

AbstractWe compared the toxicokinetics of methylmercury (MeHg) in KK‐Ay type 2 diabetic mice and C57BL/6J mice to evaluate how metabolic changes associated with diabetes affect MeHg toxicokinetics. A single dose of MeHg (0.2, 1, or 5 mg mercury/kg) was administered orally to 12‐week‐old KK‐Ay and C57BL/6J male mice. Total mercury concentrations in plasma, blood cells, whole blood, and tissues (brain, kidneys, liver, and pancreas) were measured after 4, 7, 11, and 14 days. The volume of distribution/bioavailability and the elimination rate constant per day were higher in KK‐Ay mice, while the terminal elimination half‐life was lower in almost all samples of KK‐Ay mice. The area under the curve was lower in all blood and almost all tissue samples from KK‐Ay mice. Total clearance/bioavailability was lower in all blood and tissue samples of KK‐Ay mice at all MeHg doses. These results indicate that MeHg is more rapidly absorbed by, and eliminated from, the blood cells, brain, liver, kidney, and pancreas of KK‐Ay mice under the experimental conditions. Different patterns of tissue‐to‐plasma and tissue‐to‐whole blood partition coefficients suggest that notable differences in MeHg transfer between plasma and blood cells affect its distribution in tissues of the two mouse strains. These findings are useful to understand the selective distribution of MeHg to target organs and the sensitivity to MeHg in pathological states.
Human parvovirus 4: An emerging etiological agent in cases presenting with influenza like illness
Authors: Prakash Shantanu , Shukla Suruchi , Bhagat Amit K. , Mishra Hricha , Vangala Ramakrishna , Jain Amita 
Published: October 2020

AbstractThis study was planned to study the association of parvovirus 4 (PARV4) with Influenza‐like illness (ILI). A total of 1111 patients with a clinical diagnosis of ILI and 220 healthy controls were tested for Influenza A/HINI/and H3N2, Influenza B, and PARV4. Further sequencing was done to analyze the genotype distribution of parvovirus 4. Influenza A/HINI, A/H3N2, and B were detected in 334 (30.06%), 9 (0.81%), and 10 (0.9%) cases respectively. PARV4 was detected in 135 (12.15%) cases and one healthy control. Parvovirus 4 was significantly higher in cases as compared to controls (relative risk, 30.77%; p < .0006). Sequencing of 20 isolates suggests the dominance of genotype 2 in our region.