Measurement Interval Research Articles

Development of a Comprehensive Tool for Assessing Cardiorespiratory, Muscular Strength, and Endurance Function in People With Intellectual Disabilities

Background and Aims Accurate assessment of cardiorespiratory function, muscular strength, and endurance seems necessary to be aware of, provide exercise interventions, and prevent subsequent diseases. Therefore, the current research aimed to develop a comprehensive tool for assessing cardiorespiratory, muscular strength, and endurance function in people with intellectual disabilities. Methods The current research is fundamental and practical in terms of purpose. In this study, the psychometrics of 51 specific intellectual disability tests were used to develop a tool for measuring cardiorespiratory function, muscular strength, and endurance. The face validity of the instrument through a 51-test questionnaire by 15 experts and 15 intellectually disabled educators, the content validity through a 51-test questionnaire by 15 experts, and the construct validity through a 19-test questionnaire by 243 intellectually disabled educators were examined. The tool’s reliability was checked through internal, intra-rater, and inter-rater consistency. Internal consistency was estimated by calculating the Cronbach alpha. The intra-rater and inter-rater reliabilities were also checked through the implementation of the tests by 18 people with intellectual disability in three time points and with three raters through the internal correlation index (ICC), confidence interval (CI), and standard error of measurement (SEM). Data analysis was done through exploratory and confirmatory factor analysis with AMOS version 26 and SPSS software, version 22. Results Based on the content validity ratio (CVR) estimation, 19 out of 51 tests had a content validity ratio higher than 0.49, and the rest were excluded. Regarding construct validity, 10 out of 19 tests were removed, and the final 9 tests were approved for evaluating cardiorespiratory function, muscular strength, and endurance. Exploratory factor analysis extracted three latent factors that explained 46.21% of the total variance. Confirmatory factor analysis confirmed the final construct model. The factor analysis results included KMO=0.829 and BT=4706.93 (P<0.0001). Conclusion The current study provided a special set of tests for people with intellectual disability regarding cardiorespiratory assessment (one test), strength (four tests), and muscular endurance (four tests) after psychometry of 51 specific tests. By using this set of tests, it is possible to make an accurate assessment of the physical fitness of the health of people with intellectual disability.

Devising a technique for assessing the accuracy of measuring electric motor torque

The object of this study is a technique for assessing the accuracy of measuring the torques of electric motors. This technique is based on the improvement of dynamic torque measurement processes under transient operating modes. Special attention was paid to devising adaptive methods to normalize the output signal, which take into account vibrations and nonlinearities of the measuring channel. In order to improve the accuracy of measurements under conditions when the controlled parameter has different deviations from its average value, a technique for integrating time measurement intervals was proposed. That has made it possible to generalize parameter fluctuations, providing more stable measurement results. This paper reports the simulation of the process of measuring torques of electric motors under transient operating modes and under vibration conditions. That has made it possible to test the proposed technique for estimating the variance of the methodological error, which includes the integration of measurement time intervals and makes it possible to increase the accuracy of the measurement under the conditions of transient modes in electric motor operation. An algorithm for correcting the error of the dynamic torque of the electric motor has been proposed, which allows it to be corrected. This becomes possible owing to the use of a reference measure and the proposed technique for determining the deviations of the controlled parameter of the measured quantity, as well as the automatic calibration of measuring transducers. The algorithm allows for flexible settings of the corrective action, expanding the potential of electric motor control systems. It can complement soft measurement methods, as well as adjust the threshold values of deviations under different operating modes of electric motors. This allows the measured systems to better adapt to changes in operating conditions, to adjust the specified measurement accuracy under conditions of uncertainty

Analysis of mobility robustness optimization in ultra-dense heterogeneous networks

Stable and reliable wireless connections during the user equipment's mobility are the critical issue in future mobile communication networks especially during UE's high-speed scenarios over dense heterogeneous networks (HetNets). Thus, setting an accurate value for the handover control parameters (HCPs) (i.e., time-to-trigger (TTT) and handover margin (HOM)) at different speed scenarios is required for system performance. This study proposes six different systems and each one employs different HCP settings using various mobile speed scenarios over a HetNet. Several performance metrics (i.e., received signal reference power (RSRP), handover ping-pong (HOPP), radio link failure (RLF), handover probability (HOP), handover interruption time (HOIT), and handover failure (HOF)) were used as key performance indicators (KPIs) for systems evaluations. Furthermore, 20 users were evaluated in this study using a 40 ms measurement interval. The results show a different impacts of each system on the performance of the deployed HetNet. However, System 1 (lowest TTT & moderate HOM) was the best system in term of RSRP and RLF but on the expense of HOPP. Furthermore, assigning high level of the TTT and HOM (i.e., TTT >1000 ms and HOM >8 dB) leads to 0 HOPP but high RLFs. Moreover, the best system performance in term of HOP, HOIT, and HOF were System 6 (highest TTT & high HOM) with 0.06 %, 3 %, and 0.004 %, respectively. System 4 represents the best trading off system between HOPP and RLF due to the proper configuration of the HCPs. However, the aims of evaluating several systems based on fixed HCPs over several mobile speed scenarios were to see the behaviors of the systems performance when different setting values are applied. Furthermore, this study proposes a HO self-optimization algorithm for auto-tuning the HCPs. Weighted function algorithm along with a trigger timer is used for reducing unnecessary HOs while RLF minimized by setting a trigger timer under a certain conditions when the RSRP of the serving base station (BS) goes below the received signal strength indicators (RSSI). The proposed algorithm shows a significant improvement in term of HOPP, RLF, HOP, and HOF compared to System 4 and FLC algorithm. The RSRP of the proposed algorithm is kept within acceptable range. Thus, accurate setting values for the HCPs are significant to keep the tradeoff between RLF and HOPP at the minimum level.

Structural deformation and clamping force monitoring of reconfigurable tooling motivated by strain data in aircraft assembly

The quality of aircraft assembly is mainly guaranteed by toolings which are vital to the geometrical accuracy and service performance of aviation products. In this research, a real-time monitoring system that determines the structural deformation and clamping force of reconfigurable toolings using strain data is developed to perceive the service state of the toolings. By laying fiber Bragg gratings on positioning beam and baseplate of the reconfigurable tooling, strain data of the tooling structures are gauged and transferred to curvatures. The beam and baseplate are modeled as one and two-dimensional objects respectively and shape reconstruction algorithms are established to obtain their deflection curve and surface using curvature information. Distribution of fibers is optimized to minimize the conversion error from strain to curvature. An estimation that reveals the mathematical relationship between the shape reconstruction error and measurement interval is implemented, and a mapping model from strains to clamping force of the beam is established. These algorithms are integrated into the self-developed monitoring software and undergo simulating and experimental tests. The maximum relative errors of deformation and force are 4.53% and 4.12% respectively in simulation, and 9.21% and 7.29% individually in experiment, which validates the efficiencies of the method. Tests of the monitoring system suggest that it can provide a timely and accurate sensing of the deformation and force of the tooling.

Process- and Product-Oriented Fundamental Movement Skills in Early Childhood as Predictors of Later Health-Related Fitness.

The skill domains of fundamental movement skills (FMS), emphasizing gross motor movements, including locomotor skills (LMS) and object control skills (OCS), along with process- and product-oriented measures of FMS, may predict cardiorespiratory fitness (CRF) and muscular fitness (MF) differently. This study investigates the longitudinal relationship from early childhood FMS, focusing on process-oriented LMS and OCS and product-oriented FMS, to CRF and MF in late childhood. The study involved 441 Finnish children (49.9% female; mean age at baseline, 5.5 yr) over a 6-yr period. FMS was evaluated using the Test of Gross Motor Development, third version, for process-oriented LMS and OCS, and the Körperkoordinationstest Für Kinder (KTK) was used to evaluate the product-oriented FMS. CRF was assessed through the total number of laps completed in the 20-m shuttle run test, whereas MF was measured via repetitions of curl-ups and push-ups. Employing a two-level cross-classified regression analysis and Cholesky decomposition, this study aimed to determine the contributions of product-oriented KTK and process-oriented LMS and OCS. Adjustments for variations in age, measurement intervals, and maturation were achieved through residualization. In addition, gender and body mass index were incorporated as covariates in the analysis. The analysis revealed that process-oriented LMS (CRF: Δ R2 = 0.016; MF: Δ R2 = 0.014) significantly predicted later health-related fitness, whereas OCS did not. However, KTK exhibited a better ability to predict both CRF (Δ R2 = 0.092) and MF (Δ R2 = 0.032), overshadowing process-oriented measures. In conclusion, the findings suggest that KTK, which potentially encompasses a broader spectrum of fitness elements along with FMS, more effectively predicts health-related fitness components than process-oriented FMS.

Self-assessment using 30-second chair stand test for patients with knee osteoarthritis – an intra- and inter-rater reliability study

Background We aimed to evaluate the intra-rater reliability in 30-second chair stand test (30CST) as a self-test, and the inter-rater reliability comparing a self-test with a physiotherapist-assessed 30CST for patients with knee osteoarthritis (KOA). The second purpose was to evaluate the classification ability of the 30CST as self-test to distinguish between reduced physical function and normal function. Methods Patients with KOA performed two self-tests of 30CST at home and thereafter a physiotherapist assessed the patient. Absolute agreements were presented with intraclass correlation coefficient (ICC), 95% confidence interval (CI) and standard error of measurement (SEM). Post-hoc analyses were conducted to calculate minimal detectable change (MDC). The classification ability was analysed with receiver operating characteristic (ROC)-curves and area under the ROC-curve (AUC). The significance level was p < 0.05. Results In total, 114 followed the protocol. Intra-rater and inter-rater reliability were good (ICC 0.97, CI 0.95–0.99, SEM 0.89 and ICC 0.81, CI 0.72–0.87, SEM 2.29 respectively). MDC were 2.5 stands when comparing self-test results individually and 0.23 on a group level. The MDC between self-tests and physiotherapist assessment were 6.4 stands for individual comparison and 0.59 for group comparison. The self-test was 80% likely to detect reduced physical function compared to a physiotherapist assessing physical function with 30CST (AUC = 0.79–0.80). Conclusions The results indicate that 30CST can be a reliable self-assessment of physical function in lower extremities for patients with KOA. These findings can be useful in areas such as self-screening for reduced physical function, self-assessment in digital physiotherapy, and as measurement in research projects.

Quantifying uncertainty in carbon emission estimation: Metrics and methodologies

Carbon emissions are a significant driver of global climate change in today's world. A central concern in discussing carbon emissions is the level of uncertainty associated with them. This study aims to assess the feasibility of using the Mean Squared Error (MSE) as a point estimation measure and confidence interval (CI) as an interval estimation measure to quantify the uncertainty surrounding carbon emissions. To achieve this goal, the bootstrap and Markov Chain Monte Carlo (MCMC) sampling methods were used, utilizing both classical and Bayesian inference methods to uncover the true parameter value.In the context of Bayesian inference, a 2-chain MCMC method proved to be the optimal choice for generating posterior distributions and accurately estimating the true parameter of the distribution θ. The analysis also shows that, while a CI is valuable as an evaluative measure, it does not inherently provide a quantified form of uncertainty and should not be used for quantitative uncertainty assessment. Instead, the Relative Standard Error (RSE) emerges as a promising quantitative measure for capturing the uncertainty of θ, while the percentage uncertainty offers a qualitative perspective. These combined measures provide a comprehensive toolkit for computing and communicating the uncertainty in carbon emission and emission factor values. This reinforces a move towards incorporating transparent uncertainty metrics, ensuring that stakeholders have access to reliable and accurate carbon emission values.

Bayesian estimation of the measurement of interactions in epidemiological studies.

Interaction identification is important in epidemiological studies and can be detected by including a product term in the model. However, as Rothman noted, a product term in exponential models may be regarded as multiplicative rather than additive to better reflect biological interactions. Currently, the additive interaction is largely measured by the relative excess risk due to interaction (RERI), the attributable proportion due to interaction (AP), and the synergy index (S), and confidence intervals are developed via frequentist approaches. However, few studies have focused on the same issue from a Bayesian perspective. The present study aims to provide a Bayesian view of the estimation and credible intervals of the additive interaction measures. Bayesian logistic regression was employed, and estimates and credible intervals were calculated from posterior samples of the RERI, AP and S. Since Bayesian inference depends only on posterior samples, it is very easy to apply this method to preventive factors. The validity of the proposed method was verified by comparing the Bayesian method with the delta and bootstrap approaches in simulation studies with example data. In all the simulation studies, the Bayesian estimates were very close to the corresponding true values. Due to the skewness of the interaction measures, compared with the confidence intervals of the delta method, the credible intervals of the Bayesian approach were more balanced and matched the nominal 95% level. Compared with the bootstrap method, the Bayesian method appeared to be a competitive alternative and fared better when small sample sizes were used. The proposed Bayesian method is a competitive alternative to other methods. This approach can assist epidemiologists in detecting additive-scale interactions.

«Relevant correlation» and real typology of dependences on the example of indicators of popular psychological tests

Introduction. The analysis of statistical relation between the characteristics under study is most likely the main type of analytical tasks encountered in almost any psychological study. But as our long-term experience, including my colleagues, shows in psychological research if there is no overabundance of closely related in meaning variable, between the studied indicators dominate, first of all, dependences that are far from linear.Materials and Methods. To study statistical relation, the author's method was used in the work, which makes it possible to study, along with linear dependencies, the simplest nonlinear dependencies: with a maximum and with a minimum, far from linear, monotonic and almost monotonic. This allows not only to expand the range of revealed dependencies and get rid of numerous errors in the traditional interpretation of the correlation coefficient, but also to better understand the complex psychological subject of a particular study. To demonstrate the typology of statistical dependencies, psychological data were selected for 120 subjects using 9 popular methods. The results of diagnostics according to these methods represent 114 quantitative indicators.Results. This article is devoted to the analysis of the ratio of linear and simplest nonlinear dependencies, their features and typology, their interpretation at the intersection of different intervals of dependencies measures obtained both in the study of only linear models and in the study of the simplest nonlinear dependencies, when linear dependencies become an integral part of the entire set dependencies of research interest. For example, for 6441 pairs of psychological indicators, only 17 strong linear relationships are observed, either for the MMPI test scales or for the Leary test scales. At the same time, among the “significant”, but at the same time very weak and weak dependences in the model for quarts, 29 strong simplest non-linear dependences were found (type 2 error). And among the dependencies that did not fall into the zone of significance in the model for quarts, 37 strong simplest non-linear dependencies were found (type 1 error).Discussion and Conclusions. Basically, if we restrict ourselves to the simplest non-linear dependencies, the psychologists should be most interested in dependencies with a maximum or minimum that correspond to the essence of the mental as a subject of study.

Determining the optimal sampling interval for 3D morphology measurements of different-sized natural rock joints

Efficiently studying the scale effect of surface roughness and peak shear strength of natural rock joints, especially unfilled and well-matched ones, requires an optimal sampling interval to realize cost-effective three-dimensional morphology measurements for different-sized natural rock joints with advanced non-contact optical devices. However, rationally determining such an optimal sampling interval remains controversial. To this end, inspired by digital signal processing, the optimal sampling interval is creatively determined by Shannon's sampling theorem using the Fourier series' optimum order. An empirical formula relating the joint size to the optimum order is correspondingly developed. The proposed empirical formula was found to work well under conditions of high normal stress, where the relative errors for the surface roughness and peak shear strength of series-sized natural rock joints were mostly less than 10% and 5%, respectively, but should be used cautiously under conditions of low normal stress. Furthermore, different from previous perceptions, a higher joint roughness level was discovered to not necessarily imply the need for a smaller optimal sampling interval, and conversely. The proposed empirical formula can facilitate the determination of the optimal sampling interval for measuring different-sized natural rock joints' surface morphologies in engineering practice.

Venous blood gases and electrolyte values of captive red foot tortoise (Chelonoidis carbonarius).

Blood gas analysis reflects the exchange of oxygen and carbon dioxide in the lungs. This test provides important information, since the relationship between these gases has a direct impact on the acid-basic balance in the body. Given the significance of blood gas analysis in Brazilian reptiles, this study set out to establish temperature-corrected and uncorrected reference intervals for venous blood gas measurements in Chelonoidis carbonarius, and to compare values between females and males. In this study, 19 animals were used, 8 males and 11 females. Blood samples were collected from the dorsal coccygeal vein, and the analyses were performed immediately after blood sample collection. The following parameters were measured: pH, PO2, HCO3-, TCO2, BEecf, Na, K, ICa, and Glu, and were compared between females and males. Additionally, pH, pCO2, and pO2 values were compared with and without temperature correction. Oxygen saturation and Na levels were significantly higher (p<0.05) in males. Furthermore, it was possible to infer that the lower the body temperature relative to the environmental temperature, the larger the difference in pH following temperature correction.

Use of Distributed Fiber Optic Sensors for the Monitoring of an Accelerated Pavement Test

The need to develop more efficient pavement management systems has driven continuous improvement in structural health monitoring (SHM) systems for road infrastructures. Factors such as low energy consumption, minimal disruption (small-sized and lightweight devices), resistance to environmental conditions, high durability, and sensitivity are some of the possible improvements worthy of exploration. Fiber optics appear to have several of these desired characteristics. In this context, this article presents strain measurements performed using fiber optic cables installed at various levels in pavement structures tested on the accelerated pavement testing facility at the Université Gustave Eiffel (or fatigue carousel). The results reveal that strains measured with this technology closely align with those obtained using traditional strain gauges. However, an advantage of fiber optics is that they enable distributed measurements over long distances with high precision (10 m with a measurement interval of 2.6 mm in this study). These measurements highlight a significant variability in pavement strains, seemingly attributable to the heterogeneity of pavement materials and variations in layer thicknesses. As a result of these findings, laboratory-scale investigations have been initiated to gain a better understanding of these sources of variability.

Does Number Changes of Open Manometers Filled with Pure Water Impact Wind Speeds in Venturi Tube Systems?

Fluid flow in a venturi tube (VT) is a dynamic fluid phenomenon that plays an important role in human life. Flow safety control is necessary by installing several manometers of open (MoO) containing static fluid. The study's purpose was to know the change impacts of the number of installed MoOs against flow speed characters within VTs from conditions of 1 to 2 MoOs. The research uses experimental methods. The main research equipment includes 1 blower-rheostat system, 1 VT with 8 different diameters, and 2 MoOs containing pure water. Data analysis was done using SPSS. Within measurement intervals of 4 Ω ≤ R ≤ 281 Ω and 4.58 cm ≤ d ≤ 9.45 cm, the study showed the comparison of the mean of wind speed, wind speed gradient to R (d fixed), convergent wind speed gradient to d (R fixed), and divergent wind speed gradient to d (R fixed) between 1-MoO and 2-MoO type, respectively, were1. 21E+01 ms-1 vs 1.55E+01 ms-1, -2.73E-02 ms-1Ω-1 vs -4.11E-02 ms-1Ω-1, -3.13E+02 s-1 vs -4.25E+02 s-1, and -4.31E+02 s-1 vs -4.84E+02 s-1. While its impact differences are insignificant, insignificant, significant, and insignificant, respectively.

Development of a Tool for Sizing and Technical–Financial Analysis of Energy‐Storage Systems Using Batteries

In this article, an innovative approach is presented to the sizing and technical–economic analysis of battery energy‐storage systems (BESS) designed for customers in the free energy market in Brazil. The tool enables the integration of photovoltaic (PV) energy sources and includes a comparison between the BESS + PV system and diesel generators. Integrating the computational capabilities of Microsoft Excel in the backend and the intuitive interface of PowerApps in the front end, the sizing process is based on analyzing historical energy invoices spanning at least 12 months or loading data with a 1 h measurement interval. The data discretization over the 8760 h of the year, considering the consumer's load profile, is facilitated by the PowerApps interface, providing a comprehensive visualization of the technical‐economic sizing results for BESS. A case study is conducted for a commercial load with a specific tariff for free energy market customers, revealing viable solutions for BESS compared to diesel alternatives. In this approach, it is aimed to simplify the analysis and decision‐making process, offering a valuable tool for power system engineers to evaluate sustainable and economically viable solutions in the Brazilian free energy market.

Psychoacoustic analyses of urban noise from long-term monitoring—Findings and outlook

Urban noise is usually assessed using sound pressure level indicators to assess harmful noise effects. However, studies have shown that human responses to environmental noise are driven by psychoacoustic properties even beyond sound pressure level indicators. Although the value of psychoacoustic parameters for an improved characterization of environmental noise appears plausible and has often been shown in laboratory studies, a systematic examination of psychoacoustic parameters over long measurement intervals is lacking. In the research project SALVE+, long-term acoustic measurements at several locations in a German city were subject to psychoacoustic analyses and the location-dependent behavior of psychoacoustic parameters over time was examined. The measurements were analyzed to determine the acoustic quality of urban sound beyond sound pressure level and noise annoyance. Based on statistical analyses, the psychoacoustic properties of urban locations considering their land use are discussed regarding an improved characterization of acoustic environments. Based on this approach, the suitability of psychoacoustic parameters for mapping of spatial and temporal patterns is investigated. The presentation aims to highlight the value of noise monitoring in cities and analyze opportunities for improved urban noise management that additionally considers issues such as restoration quality and health promotion.

Assessment of cyclone induced flood using microwave Synthetic Aperture Radar (SAR) data in four blocks of East Midnapore district, India

East Midnapore district is one of the flood prone regions of West Bengal, India. Geomorphological character, topographic nature and geographical location are the main causes of such kind of flood extensiveness in this region. Four most flood prone blocks of East Midnapore district are considered in this study to analyse, monitor and estimate the flood consequences. Flood intensity, duration of water logging, frequency, interval of flood and measurement of the vulnerability are the important parameters to assess the flood risk. Synthetic Aperture Radar (SAR) data has its distinct character to collect the data at the flood time even in bad weather and it can also penetrate the cloud cover and can avoid weather caused signal attenuation. European Space Agency’s (ESA) Sentinel-1 SAR before and after flood data (2021) of Vertical transmit and Vertical receives (VV) polarization has been used to monitor and detect the flood extension and assess the inundated areas. The decibel (dB) value is mentioned and speckle noise correction is applied before and after both images. By applying the threshold dB values on both images, the flood inundated areas are detected and extracted from the natural water bodies. A village wise water logged condition of this region was observed for a long time and the study reveals that total 11612.28 ha. areas are submerged due to flood inundation. For the development of the agriculture and aquaculture in terms of the local economy a special care should be taken in this low land flood, affected region.

The importance of interdigitating screw fixation of the trochlea in double plate osteosynthesis of low transcondylar distal humerus fractures: A biomechanical study

ObjectiveThe trochlea is of great importance for the stability of the elbow and its fixation in low transcondylar fractures of the distal humerus is especially challenging. The aim of this study was to determine the optimal trochlea fixation in double plate osteosynthesis of intraarticular distal humerus fractures. MethodsA low transcondylar, C3-type distal humerus fracture was created in 20 fresh-frozen human cadaveric humeri. The samples were then randomly divided into two groups of 10 specimens each. Double plate osteosynthesis was performed in both groups. In group A, the two most distal screws of the lateral plate were inserted into the trochlea fragment. In group B, these screws did not extend into the trochlea. Displacement under cyclic loading and ultimate failure loads were determined for all specimens. ResultsGroup A showed significantly less displacement under cyclic loading in each measurement interval (0.92 mm vs. 1.53 mm after 100 cycles, p = 0 0.006; 1.10 mm vs. 1.84 mm after 1000 cycles, p = 0.007; 1.18 mm vs. 1.98 mm after 2000 cycles, p = 0.008). The ultimate failure load was significantly higher in group A than in group B (345.61 ± 120.389 N vs. 238.42 ± 131.61 N, p = 0.037). ConclusionsFixation of the trochlea with interdigitating screws in double plate osteosynthesis of low-condylar type C distal humerus fractures results in superior construct stability. Level of evidencenot applicable (biomechanical)

Development of a deep learning model that predicts critical events of pediatric patients admitted to general wards

Early detection of deteriorating patients is important to prevent life-threatening events and improve clinical outcomes. Efforts have been made to detect or prevent major events such as cardiopulmonary resuscitation, but previously developed tools are often complicated and time-consuming, rendering them impractical. To overcome this problem, we designed this study to create a deep learning prediction model that predicts critical events with simplified variables. This retrospective observational study included patients under the age of 18 who were admitted to the general ward of a tertiary children’s hospital between 2020 and 2022. A critical event was defined as cardiopulmonary resuscitation, unplanned transfer to the intensive care unit, or mortality. The vital signs measured during hospitalization, their measurement intervals, sex, and age were used to train a critical event prediction model. Age-specific z-scores were used to normalize the variability of the normal range by age. The entire dataset was classified into a training dataset and a test dataset at an 8:2 ratio, and model learning and testing were performed on each dataset. The predictive performance of the developed model showed excellent results, with an area under the receiver operating characteristics curve of 0.986 and an area under the precision-recall curve of 0.896. We developed a deep learning model with outstanding predictive power using simplified variables to effectively predict critical events while reducing the workload of medical staff. Nevertheless, because this was a single-center trial, no external validation was carried out, prompting further investigation.

A Comparison of Statistical Methods to Construct Confidence Intervals and Fiducial Intervals for Measures of Health Disparities.

Health disparities are differences in health status across different socioeconomic groups. Classical methods, e.g., the Delta method, have been used to estimate the standard errors of estimated measures of health disparities and to construct confidence intervals for these measures. However, the confidence intervals constructed using the classical methods do not have good coverage properties for situations involving sparse data. In this article, we introduce three new methods to construct fiducial intervals for measures of health disparities based on approximate fiducial quantities. Through a comprehensive simulation study, We compare the empirical coverage properties of the proposed fiducial intervals against two Monte Carlo simulation-based methods-utilizing either a truncated Normal distribution or the Gamma distribution-as well as the classical method. The findings of the simulation study advocate for the adoption of the Monte Carlo simulation-based method with the Gamma distribution when a unified approach is sought for all health disparity measures.

Effects of vasodilators on beat-to-beat and every fifteen minutes blood pressure variability induced by noradrenaline infusion in rats

Increased blood pressure variability (BPV) was shown to be associated with cardiovascular morbidities and/or mortalities. There are various types of BPV depending on time intervals of BP measurements, ranging from beat-to-beat to visit-to-visit or year-to-year. We previously found that continuous infusion of noradrenaline (NA) for 14 days increased short-term BPV every 15 min in rats. The aims of this study were to examine (1) whether NA infusion increases very short-term beat-to-beat BPV, (2) the effects of azelnidipine and hydralazine on NA-induced BPV, and (3) whether baroreceptor reflex sensitivity (BRS) is affected by NA or NA plus those vasodilators. Nine-week-old Wistar rats infused subcutaneously with 30 μg/h NA were orally treated with or without 9.7 mg/day azelnidipine or 5.9 mg/day hydralazine over 14 days. BP levels were continuously monitored via abdominal aortic catheter with a telemetry system in an unrestrained condition. Standard deviations (SDs) were used to evaluate beat-to-beat BPV and BPV every 15 min which was obtained by averaging BP levels for 10-s segment at each time point. BRS was determined by a sequence analysis. Continuous NA infusion over 14 days increased average BP, beat-to-beat BPV, and BPV every 15 min, lowering BRS. Comparing the two vasodilators, hydralazine reduced BP elevation by NA; meanwhile, azelnidipine alleviated BPV augmentation, preserving BRS, despite a smaller BP reduction. Thus, NA infusion increased both very short- and short-term BPV concomitantly with impaired BRS, while azelnidipine had an inhibitory effect, possibly independent of BP-lowering, on those types of BPV and impairment of BRS.