Coefficient Correlation Research Articles

Photocatalytic decomposition of metronidazole by zinc hexaferrite coated with bismuth oxyiodide magnetic nanocomposite: Advanced modelling and optimization with artificial neural network

The objective of the present study was to employ a green synthesis method to produce a sustainable ZnFe12O19/BiOI nanocomposite and evaluate its efficacy in the photocatalytic degradation of metronidazole (MNZ) from aqueous media. An artificial neural network (ANN) model was developed to predict the performance of the photocatalytic degradation process using experimental data. More importantly, sensitivity analysis was conducted to explore the relationship between MNZ degradation and various experimental parameters. The elimination of MNZ was assessed under different operational parameters, including pH, contaminant concentration, nanocomposite dosage, and retention time. The outcomes exhibited high a desirability performance of the ANN model with a coefficient correlation (R2) of 0.99. Under optimized circumstances, the MNZ elimination efficiency, as well as the reduction in chemical oxygen demand (COD) and total organic carbon (TOC), reached 92.71%, 70.23%, and 55.08%, respectively. The catalyst showed the ability to be regenerated 8 times with only a slight decrease in its photocatalytic activity. Furthermore, the experimental data obtained demonstrated a good agreement with the predictions of the ANN model. As a result, this study fabricated the ZnFe12O19/BiOI nanocomposite, which gave potential implication value in the effective decontamination of pharmaceutical compounds.

A multiphase heat transfer model for spreading wall film coupled with solid wall temperature field

A simplified model for wall film impingement, spreading and evaporation is proposed in this work. The performance of the model was compared with experimental data. For the experimental data, a 2.8 mm diameter diesel drop at 423 K was impinged on a stainless steel wall. The solid surface and embedded temperature was recorded with time. The variation of film spread fraction, which is the ratio of the film spread diameter to the original drop diameter was also recorded with time. The present model deals with solid, liquid and gas phase physics of the wall film. An analytical expression developed previously for the heat flux from the ambient gas into the liquid gas interface, is used to represent the temperature distribution within the film. The correlation for heat transfer coefficient at the solid–liquid interface was developed and the solid temperature distribution is solved using the semi-infinite solid assumption in the 1-D coordinate system. A simplified film spread model was developed as a function of the maximum film spread fraction, which can be derived from energy conservation principles. A vapor sharing algorithm was also developed for film spreading into the neighboring computational cells. The model results were able to capture the initial rise in solid surface temperature during the initial spread of the film. However, the overall steady state temperature was slightly overpredicted. The solid embedded temperature matched well with experimental results. Variation of temperature within the film and the ambient gas temperature of the cell containing the film with time, obtained from the model was also shown.

Abstract 2308: Semi-automated Ki-67 index assessment using top-k hotspot recommendation in Ki-67 IHC stained WSIs

Abstract Ki-67 index is commonly used as a breast cancer proliferation marker. However, it is a laborious and time-consuming task for a pathologist to directly measure the Ki-67 index. Recently, automation techniques using machine learning techniques such as deep learning have been proposed. In this study, we propose a top-k hotspot recommendation method to help Ki-67 index assessment based on nuclei detection detected by a deep learning model. The dataset included a total of 32 diaminobenzidine-hematoxylin (DAB-H) Ki-67 IHC whole slide images (WSIs) of breast cancer obtained by core biopsy. Each of these WSIs was evaluated by a pathologist using the interval of the Ki-67 index estimate and the scores of 1+, 2+, 3+, and 4+. Additionally, the search area was manually designated to exclude internal control. We developed a Ki-67 index analysis model based on deep learning and image analysis. Nuclei segmentation used the StarDist model. The detected results were filtered based on nucleus size and nucleus eccentricity. The filtering threshold was determined experimentally. To recommend top-k hotspots, a coarse search is performed to move the circle region horizontally and vertically in specific units, and the top k regions based on Ki-67 index are found among areas containing more than 500 cells. Next, a fine search is performed around the k areas in detail. Finally, the top-k hotspots and each detected positive and negative cells, count of positive cells and negative cells, and predicted Ki-67 index are provided. It was confirmed that the Ki-67 score estimated for the detected top-1 hotspot and the pathologist's Ki-67 score had a correlation of Pearson correlation coefficient=0.8153, R2=0.6648. As k increased, the top-k accuracy was observed to increase from 68.75% when k = 1 and 3 to 75.00% when k = 5, based on the pathologist's score. When a pathologist reviewed 10 cases where the Ki-67 score differed from the prediction, 6 cases were judged to be worth reexamining considering the proposed hotspot and Ki-67 index, and 2 cases included stromal cells in cell detection. In two cases, the WSI was judged to be blurry. Cell analysis and top-k hotspot recommendation using deep learning and image analysis were performed on Ki-67 IHC stained WSIs and compared with the pathologist's Ki-67 score. Through semi-automatic top-k hotspot recommendation, the reliability of diagnosis can be increased as an auxiliary test to Ki-67 index assessment. Citation Format: Hyeon Seok Yang, Yunseob Hwang, Yongeun Lee, Kyungsoo Jung, Minjung Sung, Tae-Yeong Kwak, Sun Woo Kim, Hyeyoon Chang. Semi-automated Ki-67 index assessment using top-k hotspot recommendation in Ki-67 IHC stained WSIs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2308.

Translation and measurement properties of pregnancy and childbirth questionnaire in Iranian postpartum women

BackgroundPerceived care quality and patient satisfaction have been important care quality indicators in recent decades, and healthcare professionals have been influential on women’s childbirth experience. This study investigated the measurement properties of the Persian version of the Pregnancy and Childbirth Questionnaire (PCQ), designed to measure mothers’ satisfaction with the quality of healthcare services provided during pregnancy and childbirth.MethodsThis is a cross-sectional methodological study. Instrument translation, face validity, content validity, structural validity, and reliability evaluation were performed to determine the measurement properties of the PCQ’s Persian version. A backward-forward approach was employed for the translation process. Impact scores were selected based on the items’ importance to measure face validity. Content validity index (CVI) and content validity ratio (CVR) were calculated to measure content validity, and exploratory and confirmatory factor analyses were used to measure structural validity. The cluster random sampling method was used, resulting in a sample of 250 eligible women referred to the health centers of Tabriz, Iran, who were 4 to 6 weeks after giving birth. Cronbach’s alpha coefficient and Intraclass Correlation Coefficient (ICC) using a test-retest approach were used to determine the questionnaire’s reliability.ResultsThe impact scores of all items were above 1.5, which indicates a suitable face validity. The content validity was also favorable (CVR = 0.95, CVI = 0.90). Exploratory factor analysis on 25 items led to the removal of item 2 due to a factor loading of less than 0.3 and the extraction of three factors explaining 65.07% of the variances. The results of the sample adequacy size were significant (< 0.001, and Kaiser-Meyer-Olkin = 0.886). The model’s validity was confirmed based on the confirmatory factor analysis fit indicators (i.e., RMSEA = 0.08, SRMR = 0.09, TLI = 0.91, CFI = 0.93, x2/df = 4.65). The tool’s reliability was also confirmed (Cronbach’s alpha = 0.88, and ICC (95% CI) = 0.93 (0.88 to 0.95)).ConclusionThe validity and reliability of the PCQ’s Persian version were suitable to measure the extent to which Iranian women are satisfied with the quality of prenatal and intrapartum care.

Rapid and Visual Detection of Vitamin C Based on Sodium Citrate-Stabilized Silver Nanoparticles

Ensuring the vitamin C requirements are met through dietary intake or supplements is essential for health. In this study, a simple and rapid visual detection method for semi-quantitative analysis of vitamin C was proposed based on sodium citrate-stabilized silver nanoparticles (SC-AgNPs). As a validation of SC-AgNPs as a colorimetric sensor for vitamin C, color changes were observed gradually, shifting from transparent yellow to deep brown after the addition of vitamin C at various concentrations. That is also supported by an increase in absorption intensity at the peak wavelength of 417 nm, which was analyzed using a UV-Vis spectrophotometer. Based on the spectral approach method, the linear relationship between absorbance values and vitamin C is in the range of 0-4.2 mM, with a coefficient correlation of 0.99 and sensitivity of 0.95/mM. Furthermore, the feasibility of the SC-AgNPs for vitamin C detection in healthy beverages and tablet pharmaceuticals has been investigated.

LEARNING ATTITUDE, ACADEMIC INTEREST AND SELF-EFFICACY TOWARDS PHYSICS SUBJECT OF GRADE 12 SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS STUDENTS

The search for the best ways to improve student learning attitude and academic interest in physics to understand its complexity was done even before the adaptation of blended learning. With this, students self-efficacy in learning this subject matter becomes an interesting variable to explore, given that there is a change in the instruction delivery. The general purpose of this study is to determine which indicators of learning attitude and academic interest significantly influence the self-efficacy of students in the Science, Technology, Engineering, and Mathematics (STEM) strand. It also explores the significant link between learning attitude and academic interest to self-efficacy in Physics that will have an impact on students learning towards the subject. The researchers utilized a non-experimental particularly a descriptive correlational design in quantitative research using statistical tools such as mean, Pearson product moment correlation of coefficient, and linear regression. To answer the main objective of this study, a modified survey questionnaire was provided to the 100 invited respondents having a Likert 5-point scale. It was found out that negative attitudes under learning attitude and perceived ease of use with learners involvement for academic interest significantly influenced students self-efficacy in learning Physics. It further shows that academic interest is highly correlated with learning self-efficacy in this subject matter. Learning attitude is sometimes evident among the respondents while academic interest and self-efficacy showed often observable. From these results, teachers should design effective learning strategies and continue motivating their students to engage in class discussion, as they express that they can get good results in learning Physics. Students should also develop a liking for this subject matter to learn actively without having any second thoughts even though it is challenging for them. Lastly, the findings of this study have significant implications for future research in the field of Physics education. Building upon the findings, future researchers can explore other factors that influence students behavior and identify additional variables that contribute to the learning process. By doing so, future studies can be strengthened, leading to a more comprehensive understanding of the topic. KEYWORDS: Learning attitudes, academic interest, self-efficacy, learning Physics, and learners’ involvement

Efficacy and Bioavailability of silymarin on Plasma S100B Level in Cardiotoxicity-induced Rats

Cardiotoxicity is a cause of death by drug overdose. Silymarin, a cytoprotective agent used in this research to protect against induced-cardiotoxic effects in Albino Wister rats; exhibited signs of heart damage, such as elevated levels of S100B, troponin I, and CK-MB. Seventy albino Wister rats of both genders were divided randomly with each group having 10 rats. Silymarin-treated, cardiotoxic-induced, and control groups were treated for ten days. The bioavailability of silymarin was assessed, and evaluation of the efficacy of silymarin on the biomarker S100B and cardiac biomarkers (Troponin I, and CK-MB), also the histopathological assessments of the heart, liver, and kidney, in addition to the coefficient correlation of the studied biomarkers were analyzed. Research’s outcome indicated that the sets subjected to silymarin presented substantial differences in rat weight and food consumption, compared to a decrease in cardiotoxic clusters. S100B plasma level was increased in cardiotoxic groups, reduced in those subjected to silymarin, and eliminated by pretreatment with silymarin. Troponin I &amp; CK-MB expressively elevated significantly in cardiotoxic prompted rats, which declined with silymarin treatment and were prohibited in pretreatment by silymarin. The shielding characteristic of silymarin detected in end organs, like the liver, kidneys, and hearts when exposed to the cardiotoxic agent clozapine was extremely significant. The consequences of the histopathological examination of this study illustrated silymarin’s cardioprotective effects. A significant positive coefficient correlation of S100B with troponin I &amp; CK-MB was recorded. In conclusion, silymarin reduces and prevents to a larger extent the cardiotoxicity brought about by clozapine and averts heart injury. The cardioprotective efficacy of silymarin is explained by its new mechanism of action as decreasing S100B, troponin I &amp; CK-MB levels with a strong significant correlation to each other. The cardioprotective efficacy of silymarin gives promise for monitoring the cardiotoxicity adverse drug reaction induced by drugs.

THE ROLE OF MENTAL WORKLOAD IN INVESTING QUALITY OF LIFE AMONG WORKERS IN THE PHOSPHORIC ACID INDUSTRY

Introduction: Every workplace has potential hazards, one of which is psychological hazards, namely work stress. The stress felt by workers can interfere with their work activities if not controlled immediately. In Indonesia, 11.6–17.3% of the 150 million adult population suffers from stress at work. Moreover, job stress can be caused by various factors. Aims: To assess workers’ quality of work life by analyzing the relationship between mental workload and work stress. Moreover, this research investigates the individual characteristics, mental workload level, and stress level between workers. Methods: This research is a quantitative study using an observational design and a cross-sectional technique. The participants in this study were all 35 maintenance personnel. Mental workload and work stress are assessed using NASA-TLX and DASS-21 questionnaire, respectively. Results: The collected data are statistically analyzed using the Spearman correlation test and the Cramer contingency coefficient correlation test. The results showed that mental workload has a strong relationship with work stress which is in the strong category (r= 0,679) and the direction of the relationship is unidirectional. Conclusion: The conclusion of this study is that the higher the mental workload possessed by workers, the higher the level of perceived work stress. Therefore, the company can reduce work stress by conducting both individual and organizational strategies

THE IMPACT OF BRAND IMAGE ON BOOSTING SALES OF "MS GLOW" SKINCARE IN PAMEKASAN

Academic pursuit the objective of the study is to examine the impact of brand image on sales growth and quantify the extent to which a strong brand image affects sales growth. Learn This aligns with the quantitative-descriptive approach. Target population This data consists of resellers and samples of MS GLOW Pamekasan obtained from a substantial population of 25 respondents using a specific sampling quota. Exploring advanced data collection techniques to enhance analysis This questionnaire employs testing data analysis techniques such as validity, reliability, and regression tests. Data processing approaches utilize the SPSS software tool, namely version 16.0. The research findings indicate that brand image has a significant impact on increasing sales. The t-test findings indicate that the coefficient correlation is 6.484, with a t count of 6.484 and a t table value of 1.714. The significance level is 0.000, which is less than 0.05. This provides evidence to reject the null hypothesis (Ho) and accept the alternative hypothesis (Ha). The coefficient of determination (R2) indicates that the R square value is 0.646, which is statistically significant. This means that brand image (image brand) has a significant impact on sales, accounting for 64.6% of the variation. Other variables not included in the research model account for the remaining 35.4%. This. The estimated r value of 0.646 indicates a significant correlation, falling within the range of 0.60-0.799 according to table interpretation.

Quantitative measurement of the ureter on three-dimensional magnetic resonance urography images using deep learning.

Accurate measurement of ureteral diameters plays a pivotal role in diagnosing and monitoring urinary tract obstruction (UTO). While three-dimensional magnetic resonance urography (3D MRU) represents a significant advancement in imaging, the traditional manual methods for assessing ureteral diameters are characterized by labor-intensive procedures and inherent variability. In the realm of medical image analysis, deep learning has led to a paradigm shift, yet the development of a comprehensive automated tool for the precise segmentation and measurement of ureters in MR images is an unaddressed challenge. The ureter was quantitatively measured on 3D MRU images using a deep learning model. A retrospective cohort of 445 3D MRU scans (443 patients, 52±18 years; 217 female patients) was collected and split into training, validation, and internal testing cohorts. A 3D V-Net model was trained for urinary tract segmentation, and a post-processing algorithm was developed for ureteral measurements. The accuracy of the segmentation was evaluated using the Dice similarity coefficient (DSC) and volume intraclass correlation coefficient (ICC), with ground truth segmentations provided by experienced radiologists. The external cohort comprised 50 scans (50 patients, 55±21 years; 30 female patients), and the model-predicted ureteral diameter measurements were compared with manual measurements to assess system performance. The various diameter parameters of ureter among the different measurement methods (ground truth, auto-segmentation with automatic diameter extraction, and manual segmentation with automatic diameter extraction) were assessed with Friedman tests and post hoc Dunn test. The effectiveness of the UTO diagnosis was assessed by receiver operating characteristic (ROC) curves and their respective areas under the curve (AUC) between different methods. In both the internal test and external cohorts, the mean DSC values for bilateral ureters exceeded 0.70. The ICCs for the bilateral ureter volume obtained by comparing the model and manual segmentation were all greater than 0.96 (p < 0.05), except for the right ureter in the internal test cohort, for which the ICC was 0.773 (p < 0.05). The mean DSCs for interobserver and intraobserver reliability were all above 0.97. The maximum diameter of the ureter exhibited no statistically significant differences either in the dilated (p=0.08) or in the non-dilated (p=0.32) ureters across the three measurement methods. The AUCs of ground truth, auto-segmentation with automatic diameter extraction, and manual segmentation with automatic diameter extraction in diagnosing UTO were 0.988 (95% CI: 0.934, 1.000), 0.961 (95% CI: 0.893, 0.991), and 0.979 (95% CI: 0.919, 0.998), respectively. There was no statistical difference between AUCs of the different methods (p>0.05). The proposed deep learning model and post-processing algorithm provide an effective means for the quantitative evaluation of urinary diseases using 3D MRU images.

Monitoring Total Suspended Solid Distribution In Coastal Bali Area Using MODIS Satellite Data

Total Suspended Solid (TSS) is one important parameter for water quality. This research aims to analyze MODIS feasibility for identifying TSS, to identify TSS monthly patterns and annual patterns variability, and to analyze the TSS distribution patterns around Bali coastal area. Observation data of the wet season was observed in Benoa Bay on 2nd October 2013 and the dry season was observed in Perancak from July on 28th to July 31st, 2009. The comparison between observation data and satellite data was used to establish a new modification algorithm for suitable conditions around Bali coastal area. Based on research analysis, the feasibility of MODIS was different in each season. In the wet season, the coefficient correlation was (r) = 0.55 and in the dry season, it was (r) = 0.68. poor correlation in the wet season indicated the bottom effect of the area which has a shallow and heterogeneous depth. The TSS average in the wet season was 75.55 mg/l and 55.97 mg/l in the dry season. The highest value was analyzed in November (82.74 mg/l) and the lowest value in June (46.41 mg/l). During wet season, the stream volume and the stream flow rate increase and bring the TSS into coastal areas through the runoff process. The mapping patterns showed that the southern coastal area and western coastal area of Bali had a high value every month. The northern coastal had a high value only in the wet season. The characteristic of Bali river area, which is perennial and intermittent rivers caused this phenomenon. The population and Bali land-use area also affected the high TSS in these areas. Yearly patterns of TSS from 2009 to 2013 around Bali coastal areas were different every year. The highest TSS distribution observed in 2013 wet season is 87.75 mg/l. The lowest TSS distribution occurred in 2009 dry season with a value of 52.2 mg/l. The TSS tends to increase every year due to the changing in Bali land use. TSS patterns from 2009 to 2013 were dynamic every year. The El Nina and La Nino events also gave impact on the patterns. The MODIS feasibility in different locations was different depending on the characteristic of the physical property of water. The shallow and small area causes misinterpretation of the satellite reflectance. The TSS monthly patterns depended on the season and the mapping can be used to describe the sources of TSS pollution, the distribution, and the quantity of TSS in the coastal area.

Assessment of oceanographic services for the monitoring of highly anthropised coastal lagoons: The Mar Menor case study

Ocean monitoring systems are designed for continuous monitoring of the seas and oceans to track their evolution and thus anticipate environmental issues. However, they are often based on Internet of Things (IoT) systems that are expensive, hard to maintain, and offer little spatial coverage. An emerging alternative is Satellite Remote Sensing (SRS) systems that offer good geographical coverage but, as a reliable and real-time monitoring system, they also face several challenges such as environmental conditions, spatio-temporal granularity, terrain oleography, etc. This paper introduces an easy-to-use software tool to crawl water-quality data from up to 6 satellite instruments (i.e. Sentinel 3A, Sentinel-3B, NOAA VIIRS, SNPP VIIRS, Aqua MODIS, Terra MODIS) of the European Space Agency's (ESA) Coopernicus system and NASA's Marine Environmental Monitoring Service. We also provide an in-depth analysis in terms of reliability and data coverage for the chlorophyll-a (Chl-a) in a highly anthropised local/regional context like the Mar Menor lagoon (Murcia, Spain), where serious socio-environmental issues are arising due to the eutrophication process. Our results show a good linear correlation between in situ data, obtained by several Spanish public institutions since 2016, and data generated by the IRTM-NN (Inverse Radiative Transfer Model-Neural Network) algorithm of Sentinel 3 in general, reaching coefficient correlation values close to 0.9. They also show that organic matter inputs from ephemeral streams are relevant in determining Chl-a concentrations. Moreover, the temporal coverage using a single instrument is rather limited, as no data were recorded for 80% of the days studied. This figure decreases to 30% when data from the 6 satellite instruments are combined, increasing the temporal granularity of the measurements from approximately 5 to 1.5 days, suggesting the need for a combination of these systems for a robust SRS system.

The Correlation between Reading International Journal Articles on Enriching the University EFL Students’ Academic Vocabulary

The purpose of this research was to investigate the correlation of reading international journal articles on enriching students' knowledge of academic English vocabulary. This research used a quantitative method with correlation analysis and used non-random sampling to determine the sample from the population. The data of this research was obtained through questioner which consisted of 15 statements to collect the data of students' reading activity (X). Besides, the dependent variable (Y) was enriching students' knowledge of academic English vocabulary collected by using a test (multiple-choice) that consisted of 20 questions about vocabulary mastery knowledge. The participants of this research were 31 seventh-semester IAIN Bone students. Furthermore, the data collected was analyzed by using Pearson’s correlation analysis with SPSS version 25. The result of this study showed that there was significant correlation between reading international journal articles in enriching university EFL students’ academic vocabulary. It proved with the result of coefficient correlation test that showed the sig.(2-tailed) was .000 .05 and the value of Pearson correlation was .822 that could be assumed it has large of degree of correlation. It also interpreted that H0 was rejected and H1 had accepted means there was a positive and significant correlation.

Psychometric properties of the COVID-19 safety measures questionnaire in the employees of the radiation therapy center.

Due to the effect of coronavirus disease 2019 (COVID-19) outbreak on the continuation, schedule, and efficiency of radiation therapy, this study aimed to investigate the reliability and validity of the COVID-19 Safety Measures (CSM) questionnaire at the radiation therapy center. In this analytical cross-sectional study, which all personnel of the radiation therapy center (20 people) participated, the validity and reliability of the 16-item CSM questionnaire were investigated. Cultural adaptation, face validity, content validity, test-retest reliability, and internal consistency were evaluated. For face and content validity, impact score, content validity ratio, and content validity index (CVR and CVI) were calculated, respectively. Also, internal consistency and stability reliability were calculated with Kuder-Richardson (KR20) alpha and Pearson correlation coefficient and intraclass correlation (ICC), respectively. Data analysis was performed using Statistical Package for the Social Sciences (SPSS) 24 with a significant level of 5%. Out of 20 employees, 70% (14 people) were female, 75% (15 people) were married and the mean age (SD) was 32.4 (6.35) years. Scale-based Kuder-Richardson alpha, S-CVI, ICC, and confidence interval were 0.79, 0.97, 0.68, and 0.38-0.89, respectively. The validity and reliability of the 16-item CSM questionnaire were confirmed. Therefore, the application of this scale is recommended.

The Occurrence of Anxiety, Depression, and Distress among Professionals Working in Emergency Care.

Maintaining mental health is essential for professions with higher stress levels and challenging environments, including emergency specializations. In this study, the occurrence of distress, anxiety, and depression among a group of ambulance and hospital emergency care professionals was assessed (n = 202). A cross-sectional, quantitative, descriptive online survey was conducted, including the internationally validated Beck depression inventory (BDI), the perceived stress scale (PSS-14), and the State-Trait Anxiety Inventory (STAI). Statistical analyses involved descriptive statistics, the χ2-test, Mann-Whitney U test, Kruskal-Wallis test, Dunn-Bonferroni test, logistic regression (LR), Cramer coefficient (Cramer's V), Kolmogorov-Smirnov test, and Spearman's rank correlation coefficient (rs). Based on the results, female professionals are more likely to have depressive symptoms (OR = 2.6, 95% CI = 1.3-5.1), perceived stress (OR = 1.2, 95% CI = 1.2-4.1), and anxiety (OR = 2.1, 95% CI = 1.0-4.1) than male professionals. Perceived stress levels decreased proportionally with increasing years spent working in healthcare (OR = 7.4, 95% CI = 7.1-8.3). Extended work shifts of 12 or 24 h increase the risk of perceived stress and anxiety in emergency care workers (p = 0.02). Customized stress management interventions are needed to mitigate the amplified mental strain associated with gender, working years, and longer shifts in the emergency care sector to sustain their mental health and well-being.

Effect of increased resistance on dynamic compliance assessed by two clinical monitors during volume-controlled ventilation: A test-lung study

ObjectiveTo evaluate the effect of increased respiratory system resistance (RRS) on dynamic compliance (Cdyn) assessed by the NM3 monitor (Cdyn(NM3)) and the E-CAiOV module (Cdyn(ECAiOV)). Study designProspective laboratory study. MethodsA training test lung (TTL) simulated the mechanical ventilation of a mammal with 50 and 300 mL tidal volumes in three conditions of RRS [normal (RBL), moderately increased (R1) and severely increased (R2)] and a wide range of clinically relevant Cdyn. Simulations at increased RRS were paired with simulations at RBL with the same static compliance for comparisons. Pearson’s correlation coefficient and concordance correlation coefficient between the measurements at RBL with the ones with increased RRS were calculated. Bland–Altman plots were also used to evaluate the agreement of Cdyn(ECAiOV) and Cdyn(NM3) at RBL (control values) with their paired values at R1 and R2. Relative bias and limits of agreement (LOAs) were calculated and LOAs larger than 30% were considered unacceptable. Trending ability of Cdyn(NM3) and Cdyn(ECAiOV) were evaluated by polar plots. Values of p < 0.05 were considered significant. ResultsThe effect of increased RRS was more pronounced for Cdyn(ECAiOV) than for Cdyn(NM3). Unacceptable agreement was only observed in Cdyn(NM3) at R2 in the 300 mL simulation (bias = –18.3% and lower LOA = –45%). For Cdyn(ECAiOV), agreement was unacceptable for all tested RRS in both simulations, being the worst at R2 in the 300 mL simulation (bias = –54.7% and lower LOA = –100.2%). Both levels of increased RRS caused poor trending ability for Cdyn(ECAiOV), whereas the same effect was only observed for Cdyn(NM3) at R2. Conclusions and clinical relevanceIn the presence of increased RRS, Cdyn estimated by the NM3 monitor presented better capability to distinguish between changes in RRS from changes in respiratory system compliance.

Kidney volume normative values in Central European children aged 0-19years: a multicenter study.

The currently available kidney volume normative values in children are restricted to small populations from single-centre studies not assessing kidney function and including none or only a small number of adolescents. This study aimed to obtain ultrasound-based kidney volume normative values derived from a large European White/Caucasian paediatric population with normal kidney function. After recruitment of 1427 children aged 0-19years, 1396 individuals with no history of kidney disease and normal estimated glomerular filtration rate were selected for the sonographic evaluation of kidney volume. Kidney volume was correlated with age, height, weight, body surface area and body mass index. Kidney volume curves and tables related to anthropometric parameters were generated using the LMS method. Kidney volume predictors were evaluated using multivariate regression analysis with collinearity checks. No clinically significant differences in kidney volume in relation to height were found between males and females, between supine and prone position and between left and right kidneys. Males had, however, larger age-related kidney volumes than females in most age categories. For the prediction of kidney volume, the highest coefficient correlation was observed for body surface area (r = 0.94), followed by weight (r = 0.92), height (r = 0.91), age (r = 0.91), and body mass index (r = 0.67; p < 0.001 for all). This study presents LMS-percentile curves and tables for kidney volume which can be used as reference values for children aged 0-19years.

Relativistic electron ([formula omitted]) flux driving parameters over geostationary orbit using 30 years of data

The relativistic electron population at MeV energy in the Earth’s outer radiation belt at geostationary (GOE) orbit largely varies in association with solar wind disturbances. Although more researches have been done to understand the influence of different mechanisms that cause the variations in the relativistic electron flux in the region, but still the underlying physics is often complex and unclear. The present study uses relativistic electron (E>2MeV) fluxes data of Los Alamos National Laboratory (LANL) geosynchronous satellites to understand the variations and its relationship with the driving parameters. The study examines the relativistic electron fluxes variations associated with the interplanetary magnetic field (IMF) and solar wind parameters using daily averaged data from 01 January 1990 to 31 December 2018. The results indicated that the information transfer from solar wind and IMF parameters into relativistic electrons flux is dependent on the kind of driving parameter. The result identifies the rank of driving parameters based on their maximum values in the cross correlation and information transfer analysis. Thus, AE index and vsw are the dominant driving parameters for the dynamics of relativistic electrons flux at GEO orbit. The peak values of coefficient (correlation coefficients, mutual information and entropy transfer) are observed at similar lag times (τpeak). For instance, in the case of AE and Je, we have observed the maximum coefficient (associated with lag time) as follows; maximum correlation coefficient; CCmax=0.846(5days), maximum mutual information; MImax=0.803(5days), maximum transfer entropy; TEmax=0.892(5days). Such dependency analysis can help to select the model parameters that influence the relativistic electrons fluxes and improve the existed models of the dynamical system.

Accuracy of a markerless system to estimate the position of taekwondo athletes in an official combat area

ABSTRACT Obtaining kinematic analysis through a gold-standard method on sports during official competitions is challenging. Markerless tracking system can be an alternative to provide physical and technical-tactical performance data about the athletes. Therefore, we aimed to verify whether the markerless system (OpenPose) accurately tracks taekwondo athletes’ positions on the official combat area. Six taekwondo athletes performed steps and kicks in a self-selected way in two conditions: with and without an opponent. To capture the movement, seven optoelectronic (marker-based system) and two digital cameras (OpenPose markerless system) were placed around the combat area at an acquisition frequency of 120 Hz and 30 Hz, respectively. Positions of the body centre of mass and midpoint of the feet were calculated and analysed through two and three-dimensional reconstruction both. The root mean square (RMS) error comparing both methods ranged from 0.13 to 0.32 m and 0.05 to 0.16 m for two and three-dimensional analysis, respectively. Bland-Altman analysis accepted the agreement between the capture systems, and the intraclass coefficient correlation (ICC) values were classified as excellent (ICC > 0.90) in all analysis. In conclusion, the OpenPose markerless system presents promising results for its use in tracking taekwondo athletes’ position on the competition area.

Experimental and Numerical Investigation of Effect of Inclination on sCO2 Heat Transfer in a Circular Pipe

Abstract Supercritical carbon dioxide (sCO2) can be utilized as a working fluid in various thermal systems including large-scale power cycles; portable power production units, centralized coolant systems, and standalone cooling devices. However, the lack of accurate prediction tools such as heat transfer coefficient correlations and insufficient research studies about the mechanisms controlling heat transfer processes are hindering its practical realization for key energy and cooling systems. The overall objective of this study is to extend fundamental knowledge about heat transfer and fluid dynamic processes in conduits pertinent to sCO2 with an emphasis on flow direction and inclination effects. This paper presents the study on effects of gravity, buoyancy on sCO2 flow at temperatures near and away from the pseudo-critical temperature. The experimental setup consists of a high temperature and pressure sCO2 heat transfer loop and flow testing facility. Recently, researched sCO2 heat exchangers can have tubes oriented at different angles such as 45 deg or 90 deg to horizontal. For optimized design of efficient and cost-effective turbomachinery components utilizing sCO2 as the heat transfer fluid, an understanding of convective heat transfer inside a tube/pipe is equally as important as external heat transfer. This paper presents an experimental and numerical study on sCO2 heat transfer at various inclinations with angles ranging from 0 deg (horizontal) to 90 deg (vertical) along with upward and downward flow direction with different inlet temperatures. Thermocouple-based temperature measurement is utilized at multiple locations within the test section axially and circumferentially to study the temperature distributions on the tube surface. Computational fluid dynamics (CFD) simulations have been performed using ANSYS Fluent to complement experimental data. The CFD and experiment have been analyzed against the well-known Gnielinski Nusselt number correlation.