Numerical Data Research Articles

Maternal emotional availability and perinatal depressive symptoms as predictors of early childhood executive function

BackgroundThe interconnected effects of maternal perinatal depression and the early mother-infant relational quality on children's executive function development are crucial yet understudied. This study addresses this gap, focusing on how perinatal depressive symptoms and emotional availability at 6 months predict child executive function performance at age four, with an emphasis on the moderating role of emotional availability. MethodThis study included 282 mother-infant pairs recruited from the Mercy Pregnancy and Emotional Wellbeing Study, utilising repeated Edinburgh Postnatal Depression Scale measurement over the perinatal period, Emotional Availability Scales, and child executive function assessments (Shape School, NEPSY-II, Preschool Age Psychiatric Assessment, Attention Deficit Hyperactivity scale, inattentive subscale). Latent growth curve analysis incorporated controls for socioeconomic status and maternal cognitive abilities, and moderation effects were examined through multiplicative interaction terms. ResultsWe found that emotional availability influences children's executive function, specifically switching, motor inhibition, and inattentive symptoms, irrespective of maternal depressive symptom changes. This effect is further nuanced by emotional availability's moderating role in the association between depressive symptom change and switching. LimitationsThe study's limitations include a relatively small sample size for moderation analysis and the exclusion of paternal influences. ConclusionThis study is a significant step in understanding the profound influence of maternal emotional availability in infancy on child executive function development, offering new avenues for research and, if replicated, a foundation for innovative intervention approaches.

Differences in the influence of self-regulated learning levels on enhancing students’ mathematical reasoning abilities

Self-regulated learning allows students to organize, monitor, and evaluate their learning process, which has a positive impact on mathematical reasoning abilities. This research aims to analyze and describe the differences in the influence of the level of self-regulated learning on students' mathematical reasoning abilities. The research method used is quantitative, which allows the collection and analysis of numerical data to identify patterns and relationships. The method's goal is to measure variables, test hypotheses, and make generalizations from a sample to a broader population. The sample for this research was eighth-grade students in Bandung. The research instrument is in the form of 30 questionnaire statements about students' self-regulated learning. The research hypothesis, there are differences in the influence of self-regulated learning levels on enhancing students’ mathematical reasoning abilities. The research results show that there are differences in the influence of the level of self-regulated learning on students' mathematical reasoning abilities. In addition, variations were found in the influence of the level of self-regulated learning on enhancing students' mathematical reasoning abilities. This research concludes that the level of self-regulated learning plays an important role in enhancing students' mathematical reasoning abilities.

De novo urethral hypermobility at 6 months after first delivery as a risk factor for stress urinary incontinence 12 years postpartum.

The aim of the study was to analyze the association between de novo urethral hypermobility 6 months postpartum and stress urinary incontinence (SUI) symptoms at 6 months and 12 years after first delivery. Risk factors associated with the development of postnatal urethral hypermobility were also examined. A longitudinal cohort study was conducted on primigravid women, after excluding those with UI before pregnancy and/or urethral hypermobility (rotational angle ≥30°) at term. At 6 months postpartum, SUI was assessed based on symptoms and introital ultrasound performed to measure rotational angle (difference between urethro-pelvic angle at rest and at maximum Valsalva). Twelve years after delivery, women were sent a questionnaire including SUI assessment and questions on parity, current age, and body mass index. Continuous variables were compared using student's t-test and qualitative variables using chi-squared tests. A logistic regression model was constructed including variables that reached statistical significance (P < 0.05) in the univariate analysis. Of the 314 women who completed the 6-month follow-up, 265 (84.4%) were successfully contacted and completed the questionnaire at 12 years and these formed the study group. In 127 women (47.9%), de novo urethral hypermobility had developed by 6 months postpartum. There was no association between urethral hypermobility and SUI symptoms 6 months postpartum (OR: 1.17; 95% CI: 0.59-2.33). Twelve years after delivery, however, SUI was reported by 110 women overall (41.5%) and nearly half of the women who developed postnatal urethral hypermobility (61/127, 48.0%). De novo urethral hypermobility 6 months postpartum constitutes a risk factor for SUI 12 years later.

Segment-based Eulerian-Lagrangian transition method for flat nozzle spray atomization simulation

This paper presents a novel segment-based Eulerian-Lagrangian transition method for predicting the primary and secondary breakup behavior of a flat nozzle spray. It combines the Volume of Fluid (VOF) method for simulating liquid sheet disintegration and primary breakup with the Discrete Phase Model (DPM) method for secondary breakup. The VOF simulation predicts the varying thickness and local velocity characteristics of the liquid sheet from the center region to the edge region near the nozzle exit. Meanwhile, the proposed segment-based linear stability analysis in this study is capable of predicting the initial droplet variation resulting from primary breakup, considering the varying behavior of the liquid sheet from different regions. The simulation results match reasonably well with experimental data at both macroscopic and microscopic levels, effectively predicting the overall spray structure, mass flow rate, and droplet size variations across different regions with good accuracy. Both experimental and numerical data show that the Sauter mean diameter (SMD) values differ between the center and edge regions, with the edge region displaying larger droplets than the center region. This indicates that the segment-based approach is crucial for successfully predicting the spatial distributions of droplet size characteristics.

Low Muscle Strength Assessed with Dynamometry in Elderly Polypathological Patients with Acute Heart Failure: PROFUND-IC Registry.

Background: Sarcopenia is a comorbidity associated with heart failure, which aggravates its prognosis. Objectives: To analyze the differential characteristics of polypathological patients with acute heart failure (AHF) based on the presence of low muscle strength, as well as to study whether this condition is associated with a worse prognosis. Methods: An observational study of 377 patients with a diagnosis of acute heart failure from the prospective multicentric PROFUND-IC registry was carried out. The main variable is low muscle strength, which is assessed with dynamometry or prehensile strength. Epidemiological and anthropometric characteristics, as well as associated comorbidities, were analyzed. Likewise, the etiology of the AHF episode, the number of admissions in the previous year, and the NYHA scale were also included. Finally, scores on functionality, treatment established, and mortality and readmission rates were studied. Quantitative variables are described as mean, and standard deviation, and qualitative variables are expressed as absolute numbers and percentages. A descriptive and bivariate analysis was performed according to the presence of low muscle strength (handgrip <27 kg in men and <16 kg in women), using the Welch test for quantitative measures and Chi-square for qualitative variables. In addition, Kaplan-Meier curves of readmission and mortality and a logistic regression analysis were also performed. Results: 377 patients were included (56% female, mean age 83 years). 310 (82.23%) had low muscle strength. Those with low muscle strength were older (84 vs. 78 years, p < 0.001), with more cognitive impairment (11.9% vs. 0%, p = 0.021), worse functional class (p = 0.016), lower scores in the Barthel index and Rockwood scale (p < 0.001), and higher in the PROFUND index (p < 0.001). They had higher rates of readmission and mortality without statistically significant differences. The PROFUND index is significantly associated with low muscle strength (OR 1.19, CI (1.09-1.31), p < 0.001). Conclusions: Elderly polypathological patients with acute heart failure and low muscle strength have a higher PROFUND index and a lower probability of survival per year.

Study on non-uniform circumferential temperature distribution of annular fuel in the tight lattice configuration of a lead-bismuth cooled fast reactor

To guarantee the safe operation of nuclear reactors and protect fuel elements from being damaged under long-term thermal stress, analyzing the circumferential temperature distribution of the outer cladding of nuclear fuel rods in reactors with tight lattice structures is crucial. In this work, a mathematical and physical model was established through theoretical analysis to calculate the circumferential temperature distribution of the outer cladding of an annular fuel rod. The proposed model provides an analytical expression for the circumferential temperature distribution, and the key factors influencing this distribution are determined. The results of the mathematical-physical model and numerical simulation are then combined through numerical fitting. Consequently, a numerical fitting equation is obtained under the steady-state condition of the lead-bismuth reactor using annular fuel and compared with the numerical simulation data acquired via computational fluid dynamics. The results demonstrate that the proposed numerical fitting equation has high accuracy and can serve as a valuable computational tool for analyzing the circumferential temperature of fuel claddings during the operation of lead-bismuth reactors with annular fuels.

A physics-informed data-driven fault location method for transmission lines using single-ended measurements with field data validation

Data driven transmission line fault location methods have the potential to more accurately locate faults by extracting fault information from available data. However, most of the data driven fault location methods in the literature are not validated by field data for the following reasons. On one hand, the available field data during faults are very limited for one specific transmission line, and using field data for training is close to impossible. On the other hand, if simulation data are utilized for training, the mismatch between the simulation system and the practical system will cause fault location errors. To this end, this paper proposes a physics-informed data-driven fault location method. The data from a practical fault event are first analyzed to extract the ranges of system parameters such as equivalent source impedances, loading conditions, fault inception angles (FIA) and fault resistances. Afterwards, the simulation system is constructed with the ranges of parameters, to generate data for training. This procedure merges the gap between simulation and practical power systems, and at the same time considers the uncertainty of system parameters in practice. The proposed data-driven method does not require system parameters, only requires instantaneous voltage and current measurements at the local terminal, with a low sampling rate of several kHz and a short fault time window of half a cycle before and after the fault occurs. Numerical experiments and field data experiments clearly validate the advantages of the proposed method over existing data driven methods.

Performance optimization of a printed circuit heat exchanger for the recuperated gas turbine

To further improve the thermal efficiency of gas turbines, the recuperator needs to be employed and the printed circuit heat exchanger with airfoil fins meets the recuperator's requirements of high heat transfer capacity, low flow resistance, and high reliability. However, the effect of airfoil fin pitches is not clear and the structure optimization method should be developed. In this study, the heat transfer quantity and pressure drop per length of the flue gas in the airfoil channels are numerically investigated under different Reynolds numbers and airfoil fin pitches. The results show that the effect of the airfoil transverse pitch has a great effect on the performance of the flue gas and the heat transfer quantity is increased by 82.39 %–96.08 % when the transverse pitch is decreased from 6.0 mm to 1.2 mm. At the same time, the pressure drop per length is increased to 189.39–842.47 Pa/m. The heat transfer performance is varied not obviously when the airfoil longitudinal pitch is varied from 4 mm to 15 mm. Based on the numerical data, the multiple-objective genetic algorithm combined with the backpropagation neural network is proposed for the performance predictions and optimizations. The corresponding Pareto front is obtained and the technique for order preference by similarity to the ideal solution method is employed to obtain the optimal point. Under the current conditions, the heat transfer quantity of the optimal point is 521.25 kW/m2, which is decreased by 34.5 % compared to the highest value, and the pressure drop per length of the optimal point is 108.45 Pa/m, which is decreased by 85.2 % compared to the highest value.

Performance Evaluation of Structural Health Monitoring System Applied to Full-Size Composite Wing Spar via Probability of Detection Techniques.

Probability of detection (POD) is an acknowledged mean of evaluation for many investigations aiming at detecting some specific property of a subject of interest. For instance, it has had many applications for Non-Destructive Evaluation (NDE), aimed at identifying defects within structural architectures, and can easily be used for structural health monitoring (SHM) systems, meant as a compact and more integrated evolution of the former technology. In this paper, a probability of detection analysis is performed to estimate the reliability of an SHM system, applied to a wing box composite spar for bonding line quality assessment. Such a system is based on distributed fiber optics deployed on the reference component at specific locations for detecting strains; the attained data are then processed by a proprietary algorithm whose capability was already tested and reported in previous works, even at full-scale level. A finite element (FE) model, previously validated by experimental results, is used to simulate the presence of damage areas, whose effect is to modify strain transfer between adjacent parts. Numerical data are used to verify the capability of the SHM system in revealing the presence of the modeled physical discontinuities with respect to a specific set of loads, running along the beam up to cover its complete extension. The POD is then estimated through the analysis of the collected data sets, wide enough to assess the global SHM system performance. The results of this study eventually aim at improving the current strategies adopted for SHM for bonding analysis by identifying the intimate behavior of the system assessed at the date. The activities herein reported have been carried out within the RESUME project.

Child Health Dataset Publishing and Mining Based on Differential Privacy Preservation

With the emergence and development of application requirements such as data analysis and publishing, it is particularly important to use differential privacy protection technology to provide more reliable, secure, and compliant datasets for research in the field of children’s health. This paper focuses on the differential privacy protection of the ultrasound examination health dataset of adolescents in southern Texas from three aspects: differential privacy protection with output perturbation on basic statistics, publication of differential privacy marginal histogram and synthesized data, and a machine learning differential privacy learning algorithm. Firstly, differential privacy protection results with output perturbation show that Laplace and Gaussian mechanisms for numerical data, as well as the exponential mechanism for non-numerical data, can achieve the goal of protecting privacy. The exponential mechanism provides higher privacy protection. Secondly, a differential privacy marginal histogram with four attributes can be obtained with an appropriate privacy budget that approximates the marginal histogram of the original data. In order to publish synthetic data, we construct a synthetic query to obtain the corresponding differential privacy histogram for two attributes. Further, a synthetic dataset can be constructed by following the data distribution of the original dataset and the quality of the synthetic data publication can also be evaluated by the mean square error and error rate. Finally, consider a differential privacy logistic regression model under machine learning to predict whether children have fatty liver in binary classification tasks. The experimental results show that the model combined with quadratic perturbation has better accuracy and privacy protection. This paper can provide differential privacy protection models under different demands, which provides important data release and analysis options for data managers and research organizations, in addition to enriching the research on child health data releasing and mining.

British defense policy against ISIL in Iraq and Syria under David Cameron 2014-2016

The purposes of this research to investigate how the UK's decision to engage militarily against ISIL, under Operation Shader, aligns with the principles of neoclassical realism. This research employs a qualitative methodology. The qualitative descriptive approach employed is one of data analysis. This approach is not limited to the presentation of numerical or statistical data. Instead, it focuses on the interpretation and description of the phenomenon under investigation, employing a narrative format. This approach prioritizes the collection of empirical evidence derived from observational studies, interviews, and the analysis of various documents. The results are how UK and US continues to defend itself against ISIL's presence and movements and seeks new strategies to drive them out of the international system.

Exploring double-diffusive convection in ferromagnetic Carreau nanofluid with magnetic dipole: Insights for solar thermal systems over plate, wedge, and stagnation

The use of ferromagnetic Carreau nanofluid in solar thermal systems enhances heat transfer and magnetic effects, optimizing solar collector design, improving solar power efficiency, and innovating nanofluid-based solar heaters and energy storage. Magnetic nanostructures significantly impact viscosity and thermophysical properties, influencing Ferrofluids' magneto-viscous nature. The investigation illustrates double-diffusive convection in radiative flow past three different geometries of ferromagnetic Carreau nanofluid, emphasizing the novel discussion of diffuse-thermal and thermo-diffusion impacts. Numerical solutions are obtained using the shooting technique with the Runge-Kutta fourth-order approach. Graphs and numerical data in tables depict the impacts of pertinent parameters. The study reveals that the radiation parameter, Soret parameter, and Dufour parameter contribute to temperature improvement as they are enhanced. These findings showcase the potential for advancing solar thermal systems through the utilization of ferromagnetic Carreau nanofluid, offering insights for sustainable solar energy applications. As the thermophoresis parameter increases from 0.001 to 0.005, the percentage change in the Nusselt number decreases for all three locations: Plate (0.90 %–0.66 %), Wedge (0.77 %–0.62 %), and Stagnation Point (0.62 %–0.54 %). This indicates that while the absolute values of the Nusselt numbers increase, the rate of change becomes smaller as increases.

Computerized Adaptive Testing for the Berg Balance Scale Improves Measurement Efficiency Without Compromising Precision in People With Stroke.

Objectives of this study were to confirm the Berg Balance Scale's (BBS) measurement properties and unidimensionality with an item response theory analysis in persons with subacute and chronic stroke and examine the precision and efficiency of computerized adaptive testing (CAT). Data were obtained from 519 ambulatory persons with subacute and chronic stroke in 2 retrospective databases. A principal component analysis (PCA) of residuals was used to evaluate unidimensionality. BBS fit to a rating scale model versus a partial credit model was examined and item parameters were generated for CAT calibration. Person measures from all 14 items were defined as actual balance ability. BBS CAT simulations were used to examine changes in measurement precision with increasing number of items administered and a precision-based stopping rule (0.5 logit standard error (SE) threshold). A PCA of residuals supports the BBS's unidimensionality and Rasch analysis supports using the rating scale model for measurement. Maximum precision for BBS CAT was SE = 0.40 logits when administering all items. BBS CAT estimated balance ability was highly correlated with actual ability when 4 or more items were administered (r > 0.9). Precision was within 0.5 logits when 5 or more items were administered (SE < 0.48 logits). BBS CAT estimated balance ability was highly correlated with actual ability (r = 0.952) using a precision-based stopping rule. The average number of items administered with the precision-based stopping rule was 5.43. The BBS is sufficiently unidimensional and the rating scale model can be used for measurement. BBS CAT is efficient and replicates the full instrument's reliability when measuring balance ability in ambulatory persons with subacute and chronic stroke. Future work should aim to enhance the interpretability of measures to facilitate clinical decision making. BBS CAT provides an efficient way of measuring balance ability for individuals in stroke rehabilitation giving clinicians more time with patients.

Association between financial anxiety and subjective health and physical fatigue perceptions among mothers of 18-month-old infants

Objective Poverty is a factor that affects children's health through its role in parental depression and stress. While the association between financial status and depression or quality of life scores of mothers has been previously reported in Japan, no study has focused on mothers' subjective health and physical fatigue perceptions. This study aimed to examine the relationship between mothers' financial anxiety and subjective health and physical fatigue perceptions.Methods We conducted a survey in parents attending routine health checkups for their 18-month-old infant in a single area of City A between November 2017 and October 2019. After excluding those for whom the required analysis data were missing, we analyzed data from 779 parents who responded to the survey and consented to the use of their children's health checkup data. The response variables were maternal subjective health and physical fatigue perceptions, and the explanatory variables were the presence of financial anxiety in mothers at their child's 3- or 18-month health checkups and financial anxiety situation in both periods. Financial anxiety was classified into four groups according to status at the 3- and 18-month time points. The independence of the qualitative variables among these four groups was verified using Fisher's exact test, and the relationship between financial anxiety and maternal subjective health and physical fatigue perceptions was evaluated using logistic regression analysis.Results Financial anxiety was present in 54 mothers (6.9%) and 46 mothers (5.9%) at the 3- and 18-month checkup, respectively. Analysis of financial anxiety in both periods showed that 695 mothers (89.2%) had no financial anxiety at either time point, 30 (3.9%) had financial anxiety only at the 18-month checkup, 38 (4.9%) had financial anxiety only at the 3-month checkup, and 16 (2.1%) had financial anxiety at both time points. At the 18-month checkup, the odds ratios of poor subjective health and severe physical fatigue perceptions were 3.85 (95% confidence interval [CI]; 1.34-11.05) and 6.58 (95% CI; 2.18-19.85), respectively, among the mothers who had financial anxiety at both time points compared to those who had no financial anxiety at either time point.Conclusion Financial anxiety may affect mothers' health. Therefore, mothers should be provided with solution-oriented support geared toward mitigating financial anxiety, in coordination with affiliated organizations, if financial anxiety is detected.

Music therapy and anhedonia: A case study

Anhedonia is a reduced ability to experience pleasure or enjoy everyday activities. It is a common symptom of many chronic and mental illnesses. This case study outlines a four-month music therapy program with one individual experiencing anhedonia. In this study, the authors investigated whether brief, daily, guided musicking activity would lead to increased anticipatory and consummatory pleasure for the case study participant. Analysis of numerical data supported this hypothesis. Subsequent analysis of descriptive data articulated key features of the action and experience of the guided musicking process for both the music therapy participant and guide. Findings from this study indicated that music within a therapeutic relationship supported positive outcomes in this case. Further research is needed to understand the potential impact of guided musicking activity for other people with anhedonia.

Developing a new measure of retrospective body dissatisfaction: links to postnatal bonding and psychological well-being

ABSTRACT Background Pregnancy is a transformative time for women and their bodies, and therefore thoughts and feelings about the body understandably change during this period. While previous research has established the impact of body dissatisfaction on factors like antenatal attachment and maternal mental health, there is a notable gap in understanding its long-term effects on postnatal factors. This is often due to high attrition rates in longitudinal studies. Using retrospective measures could address this issue, however a measure of retrospective pregnant body dissatisfaction has not yet been identified. Aims This paper aimed to create a retrospective measure of pregnancy body dissatisfaction by adapting a previously validated measure. It also aimed to investigate the relationship between retrospective accounts of body dissatisfaction during pregnancy and postnatal anxiety, depression, and bonding. Method Cross-sectional online survey data was collected from women postnatally (N = 404). Findings An exploratory and confirmatory factor analysis identified a two-factor model of retrospective body dissatisfaction, adapted from the Body Understanding Measure for Pregnancy Scale, which was equivalent to two of the original subscales. Using this factor structure, linear regressions demonstrated that higher levels of retrospective pregnant body dissatisfaction were associated with elevated rates of postnatal anxiety and depression and lower bonding scores. Conclusions This study successfully established a measure for assessing retrospective pregnant body dissatisfaction, potentially aiding future research. Additionally, it has highlighted the link between pregnant body dissatisfaction and postnatal levels of depression, anxiety, and bonding. Thus, improving the pregnant bodily experience may have the potential to enhance the postnatal experience.

Experience of a centre of excellence in hip fractures of the elderly in Colombia: influence of time-to-surgery on inpatient mortality and complications.

To analyse the time-to-surgery of a centre of excellence in hip fractures of the elderly and its influence on inpatient mortality and postoperative complications. A cross-sectional cohort study was conducted. The sample universe consisted of 4,364 patients admitted to a university clinic in Chía, Colombia during the year 2018 to 2023 with ICD-10 diagnoses corresponding to femur fractures. After eliminating duplicates and application of inclusion and exclusion criteria, the final sample included was 269 patients. Qualitative and quantitative variables were analysed, such as: sex, age, age group, type of fracture, type of surgical procedure, time-to-surgery, time to discharge, inpatient mortality and postoperative complications. The mean time-to-surgery from admission was 70.16h or 2.92 days (IQR 37-87). Patients were divided into three subgroups of time in which they were taken to surgery: <24h (11.89%), 24-48h (33.82%) and > 48h (54.27%). The overall mortality rate was 1.85% for a total of five deceased patients, two of whom belonged to the 24-48-hour group and three to the > 48h group. Higher rates of postoperative complications were observed in the > 48-hours group (n: 39, 14.49%), followed by the 24-48-hour group (n: 25, 9.29%) and the < 24-hour group (n: 7, 2.6%). Patients operated for a hip fracture in > 48h since admission had a slightly higher rate of postoperative complications. No significant difference was observed regarding inpatient mortality when compared to the 24-48-hour group.

Vibration-based damage detection of beams using Hybrid Genetic Algorithm with combined l0 and l1 regularization

Vibration-based damage detection is an effective way of identifying beam damages before they become severe and potentially catastrophic. This paper introduces a novel and robust method for detecting multiple cracks in beams using a Hybrid Genetic Algorithm (HGA). The objective function of the proposed method, based on dynamic properties, can be employed with partial modal information and is enhanced by including the initial residuals between numerical and experimental models along with combined l0 and l1 regularization. This enhancement mitigates the impact of limited modal data, experimental noise, and modeling inaccuracies. Additionally, a method of selecting an appropriate regularization parameter by analyzing residual and solution norm curves is presented. The performance of the proposed method is evaluated and verified using both numerical simulations and experimental studies on a steel cantilever beam under four damage scenarios. In the experimental study, natural frequencies and mode shapes were determined under ambient vibration conditions using Enhanced Frequency Domain Decomposition (EFDD) and the Stochastic Subspace Identification (SSI) method. Finite element models of the beam were developed in ABAQUS software for numerical analysis, and a comparative study of numerical and experimental data was conducted. The proposed approach successfully identifies, locates and quantifies single and multiple damages in the beam, demonstrating its reliability and effectiveness, particularly in scenarios with limited modal data and significant experimental noise.

Perceptions Toward Telemedicine of Health Care Staff in Nursing Homes in Northern Germany: Cross-Sectional Study.

Digitalization in the German health care system is progressing slowly, even though it offers opportunities for improvement of care. In nursing homes, most of the staff's work is paper based. Following the pandemic, there has been a decrease in the use of telemedicine applications. To ensure long-term implementation, the views of users, in this case nurses, are of interest. This cross-sectional study was conducted to describe which digital applications are already being used at inpatient care facilities, the attitude of nurses toward telemedicine, and for which areas the use of telemedicine in the facilities is considered appropriate by the participants. All inpatient care facility staff in Schleswig-Holstein were invited to participate in the survey from August 1 to October 31, 2022. The questionnaire consists of 17 determinants that ask about the attitude, use, and possible applications of telemedicine. In addition to a descriptive analysis, the influence of the general attitude toward telemedicine on various determinants was examined using the Fisher exact test for nominal variables and Spearman correlation coefficient for metric variables. A total of 425 caregivers participated in the survey. Of these respondents, 10.7% (n=41) currently used video consultations, and 76.1% (n=321) of the respondents were in favor of video consultations being practiced in training. Furthermore, 74.8% (n=312) of the respondents would attend a training on telephone medical consultation. Respondents indicated that video consultations have a small added value compared to asynchronous telemedicine (eg, sending photos). However, video consultations were perceived as somewhat less time-consuming than other communication channels. Video consultations are perceived as most useful for clarifying urgent problems. The respondents estimated that one in five paramedic calls at their facilities could be reduced through telemedicine approaches. It was important to the participants that telemedicine is as simple as possible and that there is a high level of data security. Although many caregivers have a positive attitude toward telemedicine and perceive its advantages, communication channels such as video consultation are still used infrequently in care facilities. To promote the use of telemedicine applications, it is important to emphasize their benefits. The presumed saving of paramedic calls thus represents a benefit, and it is crucial to train caregivers in the use of telemedicine to avoid uncertainties in dealing with the newer technologies. It is important to give them enough time and repetitions of the training.

Real-Time Calculation of CO2 Conversion in Radio-Frequency Discharges under Martian Pressure by Introducing Deep Neural Network

In recent years, the in situ resource utilization of CO2 in the Martian atmosphere by low-temperature plasma technology has garnered significant attention. However, numerical simulation is extremely time-consuming for modeling the complex CO2 plasma, involving tens of species and hundreds of reactions, especially under Martian pressure. In this study, a deep neural network (DNN) with multiple hidden layers is introduced to investigate the CO2 conversion in radio-frequency (RF) discharges at a given power density under Martian pressure in almost real time. After training on the dataset obtained from the fluid model or experimental measurements, the DNN shows the ability to accurately and efficiently predict the various discharge characteristics and plasma chemistry of RF CO2 discharge even in seconds. Compared with conventional fluid models, the computational efficiency of the DNN is improved by nearly 106 times; thus, a real-time calculation of RF CO2 discharge can almost be achieved. The DNN can provide an enormous amount of data to enhance the simulation results due to the very high computational efficiency. The numerical data also suggest that the CO2 conversion increases with driving frequency at a fixed power density. This study shows the ability of the DNN-based approach to investigate CO2 conversion in RF discharges for various applications, providing a promising tool for the modeling of complex non-thermal plasmas.