Deviation Of Pressure Research Articles

Many-objective optimisation tool for the design of district metered areas in pumped water distribution networks

Abstract The establishment of district metered areas (DMAs) is a highly effective method to mitigate operational management difficulties and enhance the efficiency of water distribution networks (WDNs). There are several objectives associated with the DMA's design that are contingent upon the network parameters that are affected by its formation. Two previous studies considered DMA design as a three-objective problem (operational cost, average pressure and water age) and a four-objective problem (design cost, pressure deviation, resilience index (RI) and demand shortfall) for pumped and gravity networks, respectively. The problems were addressed through the implementation of a multi-phase DMA design methodology using the NSGA-II and NSGA-III optimisation tools, respectively. The present work builds upon previous research by simultaneously considering five objectives in DMA design (i.e. design cost, operational cost, RI, average pressure and water age) using the NSGA-III optimisation tool in pumped water networks. In this extended approach, the pump's role in meeting nodal demands eliminates the necessity of including demand shortfall as one of the objectives. The proposed methodology has been evaluated on two benchmark networks, demonstrating its capability to identify DMA alternatives and provide solutions based on user preferences. Finally, the obtained results are compared with the previous study's findings.

Measurement of Critical Temperatures, Critical Pressures and Densities of Acetone–Water Solutions for Simulation

Critical temperature, critical pressure and P–T–ρ–X data of acetone–water solutions with water mole fractions in a range of 0–60% were measured to provide fundamental data for CFD simulations. Critical temperatures were determined via observing critical opalescence in fused quartz capillary tubes. Meanwhile, critical pressures were measured by heating acetone–water solutions to its critical temperature in an autoclave. The standard deviations of critical temperature and critical pressure were 0.55 K and 0.029 MPa, respectively. The results indicate that only one phase exists during mixing of acetone with water. Moreover, P–T–ρ–X data under 15 and 20 MPa in the temperature range of 460–550 K were measured in the autoclave. The relative deviation of density was 0.32%. Volume-translated Peng-Robinson and Soave–Redlich–Kwong state equations were used to illustrate the P–V–T–X relationship of acetone–water solutions, and the Peng–Robinson state equation with an average absolute relative deviation of 1.19% between fitting and experimental densities was found more accurate.

Research on hybrid power load matching control method of new energy pumping machine

In order to improve the energy saving effect of new energy pumping machine, the power matching energy saving control of wind energy, electric energy and pumping machine load should be carried out when the actual wind speed is lower than the rated wind speed of the system. In this paper, according to the wind power hybrid transmission system, we study the load matching energy saving control strategy and method that takes into account the simultaneous change of wind speed and load, and propose the hybrid power load matching adaptive energy saving control strategy based on the cascade controller. In the strategy, the motor torque control method is used to eliminate the pressure deviation and realize the system pressure tracking load matching adaptive control, while keeping the motor output torque stable.

Variational RANS modeling of hydraulic jumps

The hydraulic jump is a phenomenon which frequently appears in nearshore, estuarine and riverine regions; it plays a major role for example in the development and migration of sand waves in mobile beds, and in controlling the propagation of infra-gravity water waves from the nearshore into the river through bar-built, shallow estuaries. Although the prediction of these natural flows becomes crucial in many circumstances, it is difficult because hydraulic jumps are complex flows, and their modeling is far from simple. The steady-state hydraulic jump may be undular or broken, and their physical properties differ significantly. Undular jump profiles are dominated by the deviation of the fluid pressure from hydrostatic conditions, with turbulence playing a secondary role. In contrast, broken hydraulic jumps are determined by the differential advection of momentum due to breaking, and turbulence stresses. Between both types, there is a complex transition involving the interaction of non-hydrostaticity and turbulence, which is difficult to mimic with depth-averaged models. Simulations of these flows are typically conducted by resorting to vertically-averaged models either using the Saint-Venant or the Serre-Green-Naghdi equations, but none of them are fully satisfactory. In this work, an alternative approach for hydraulic jumps is proposed by developing a variational Reynolds-Averaged Navier-Stokes (RANS) model which uses Kantorovich-Krylov expansions of the flow variables, and a novel depth-averaged, eddy viscosity approach suitable for non-hydrostatic flows. The model is validated through results of simulations of both undular and broken jumps compared against detailed experiments. New experiments were conducted in a simplified bar-built shallow river inlet; the variational RANS model was found to reproduce well the flow profile over the bar, the hydraulic jump position and dynamic pressures over the bar surface.

Study on Mine Ventilation Resistance Coefficient Inversion Based on Genetic Algorithm

The frictional resistance coefficient of ventilation of a roadway in a coal mine is a very important technical parameter in the design and renovation of mine ventilation. Calculations based on empirical formulae and field tests to calculate the resistance coefficient have limitations. An inversion method to calculate the mine ventilation resistance coefficient by using a few representative data of air flows and node pressures is proposed in this study. The mathematical model of the inversion method is developed based on the principle of least squares. The measured pressure and the calculated pressure deviation along with the measured flow and the calculated flow deviation are considered while defining the objective function, which also includes the node pressure, the air flow, and the ventilation resistance coefficient range constraints. The ventilation resistance coefficient inversion problem was converted to a nonlinear optimisation problem through the development of the model. A genetic algorithm (GA) was adopted to solve the ventilation resistance coefficient inversion problem. The GA was improved to enhance the global and the local search abilities of the algorithm for the ventilation resistance coefficient inversion problem.

Study on force chain evolution of rice straw with different length during vibrational compression

This paper explores the mechanism of force chain evolution and voidage change under vibrational and non-vibrational compression conditions of rice straw of different lengths. Simulations were used to explore the force chain evolution and voidage variation mechanism under different conditions. The results show that under non-vibrational compression, the strong force chain passes from top to bottom in vertical direction and from center to periphery in tangential direction. Under vibrational compression, the force chain passes from top and bottom to center in vertical direction and the force chain evolves from outer ring to interior and exterior in tangential direction. The number of strong chains, voidage and standard deviation of the mean pressure under vibratory compression are lower than the values under non-vibratory compression. Vibration promotes stress transfer and enhancement, velocity enhancement and density enhancement. This study analyzes the mechanical properties of different lengths straw during vibrational and non-vibrational compression from a detailed viewpoint.

Application of Digital Twin in the Industry of Axial Hollow-Wall Pipes

With the increasing demand for automation in agriculture, more and more researchers are exploring the application of digital twin in agricultural production. However, existing studies have predominantly focused on enhancing resource utilization efficiency and improving irrigation control systems in agricultural production through the implementation of digital twins. Unfortunately, there is a noticeable research gap when it comes to applying digital twins specifically to buried water conveyance pipelines within an agricultural irrigation infrastructure. Focusing on the long-term performance requirements of buried pipelines in agricultural irrigation and drainage, this study established a digital twin system for the industry of axial hollow-wall pipes with an outer diameter of 200 mm, specifically designed for this field of operation. The system was used to optimize the end-forming process of axial hollow-wall pipes, resulting in improved leak tightness under internal pressure and angular deflection of the pipes. The study suggests that the most effective method for the end-forming process of axial hollow-wall pipes is to heat the pipe for 60 s at the ambient temperature of 15 °C, with heating temperatures of 225 °C on both the inner and outer sides. Additionally, preheating the stamping equipment to 70 °C and controlling the cooling temperature, during pipe detachment, to between 35 °C and 45 °C is recommended. In terms of the leak tightness under internal pressure and angular deviation, the study found that increasing the thickness of the protruding end of the sealing ring to 16 mm, and shortening the chamfer length to 20 mm, while maintaining the same slope, can enhance the sealing effectiveness of the pipeline interface. The implementation of the digital twin system improves the production efficiency of the hollow pipe production line during the end-forming process, resulting in a yield rate of the pipe of up to 95% for qualified products. Moreover, the system provides intelligent closed-loop feedback which ensures the long-term operation and maintenance of the pipelines, making it easier to identify problems and implement design improvements. By doing so, it contributes to ensuring the long-term stability of related agricultural production.

Decision support system for power cable insulation vulcanization production line management

The paper proposes a structural model of a decision support system for controlling a cable insulation continuous vulcanization line. The proposed decision support system is based on a mathematical model of the cable insulation continuous vulcanization technological process, a database, and a mode correction algorithm. The DSS will make it possible to quickly develop a new regime in case of using new materials or structures, as well as to correct the current regime in case of unplanned changes during the production process. The core of the DSS is the proposed mathematical model, which is based on conservation laws and is presented as a system of differential equations closed by boundary conditions. The vulcanization process is described taking into account the temperature-time dependence of the kinetic parameters, which made it possible to take into account the uneven heating of the cable, both in the radial direction and along the length. The numerical implementation of the differential mathematical model made it possible to carry out a systematic analysis of the nature of the processes in the vulcanization pipe and to evaluate the influence of various technological, structural and material parameters on the cable insulation vulcanization completion degree. As a result of the analysis, significant parameters were identified that significantly affect the vulcanization process completion degree. Based on the obtained numerical results, technological parameters dependence technological surfaces on the geometry of the product and the properties of the materials used were constructed, a regression mathematical model was proposed that allows determining the values of the process control parameters without resorting to the use of a differential mathematical model. Based on the results of the analysis, an algorithm for correcting the technological regime is proposed, taking into account only significant process parameters. The proposed algorithm allows you to adjust the value of the isolation rate, depending on external influences and deviations from the specified parameters. The results of the study can be used in the production of cable and wire products with vulcanizable insulation, when it is necessary to quickly select the optimal technological mode, take into account changes in the cable design, properties of the insulation material, as well as possible pressure deviations inside the vulcanization pipe.

Numerical simulation of non-isothermal supercritical water flow in ground pipeline and wellbore: An interactive sensitivity analysis and injection parameters optimization

Supercritical water injection is promising in enhanced heavy oil recovery, in which precise prediction and regulation of bottomhole parameters are the prerequisite for improving the recovery efficiency. However, dramatically changing thermophysical properties make it difficult to calculate the hydraulic and thermal resistances of supercritical water flow in ground pipeline and wellbore. In this work, a comprehensive mathematical model was established to simulate the non-isothermal flow of supercritical water from boiler outlet to bottomhole. Modified correlations of friction coefficients and convective heat transfer coefficients respectively developed for vertical and horizontal flow of supercritical water were coupled in momentum and energy conservation equations to calculate the hydraulic and thermal resistance. The model was validated by oilfield and laboratory data with the relative deviations of pressure and temperature less than 2%. The interactive sensitivity analysis was carried out by response surface method for injection parameters optimization. The results indicated that the heat loss in ground pipeline was comparable to that in wellbore once it reached 10 times longer than wellbore and should be taken into consideration. Increasing mass flux was found to be efficient for reducing the heat loss resulted from the decline of wellbore insulation. But there existed a matching combination of injection pressure and mass flux that making bottomhole temperature the highest. For a typical injection case with a poor insulation wellbore and limited injection temperature, a combination of high mass flux and low injection pressure was recommended for achieving targeted bottomhole temperature due to its high thermal efficiency.

Predictive ability of visit-to-visit blood pressure indices for adverse events in patients with non-valvular atrial fibrillation: Subanalysis of the J-RHYTHM Registry

We previously reported that standard deviation (SD) of systolic blood pressure (SBP), an index of BP variability, and SBP-time in target range (TTR), an index of BP consistency, were significantly associated with adverse events in patients with non-valvular atrial fibrillation (NVAF). Thus, this study aimed to compare predictive ability for adverse events among visit-to-visit BP variability/consistency indices using data from the J-RHYTHM Registry.Of 7406 outpatients with NVAF, 7226 (age, 69.7 ± 9.9 years; men, 70.7%), in whom BP was measured 4 times or more (14.6 ± 5.0 times) during the 2-year follow-up period or until occurrence of an event, were included. As BP consistency for target SBP between 110 and 130 mmHg, SBP-TTR by the Rosendaal method and SBP-frequency in range (FIR) were calculated. Predictive ability was expressed by the area under receiver-operating-characteristic curve (AUC). AUCs of SBP-TTR and SBP-FIR for adverse events were compared with those of SBP-SD by the DeLong's test.SBP-SD, SBP-TTR, and SBP-FIR were 11.0 ± 4.2 mmHg, 49.5 ± 28.3%, and 52.3 ± 23.0%, respectively. AUCs of these indices for thromboembolism, major hemorrhage, and all-cause death were 0.62, 0.64, and 0.63 for SBP-SD; 0.56, 0.55, and 0.56 for SBP-TTR; and 0.55, 0.56, and 0.58 for SBP-FIR; respectively. AUCs of SBP-SD were significantly larger than those of SBP-TTR for major hemorrhage (P = 0.010) and all-cause death (P = 0.014), and SBP-FIR for major hemorrhage (P = 0.016).Among visit-to-visit BP variability/consistency indices, predictive ability of SBP-SD for major hemorrhage and all-cause death was superior to that of SBP-TTR and SBP-FIR in patients with NVAF.

EFFECT OF COVID-19 ON BLOOD PRESSURE VARIABILITY IN HYPERTENSIVE PATIENTS

Objective: To investigate the influence of COVID-19 on blood pressure variability in hypertensive patients with known subclinical organ damage (SCOD) previously assessed by evaluation of brachial artery Flow Mediated Dilatation (FMD), carotid artery Intima Media Thickness (IMT), left ventricular mass indexed to BSA (LVMI), E/e` ratio, left atrial volume indexed to BSA (LAVI). Design and method: We assessed 108 hypertensive patients who had SARS-CoV-2 infection in the previously 3 months before evaluation. All subjects included where evaluated for the presence of SCOD in the last 12 months before COVID-19 and underwent a 24-hour noninvasive ABPM on a working day, performing usual daily activities and avoiding heavy physical exercise. BP and heart rate readings were obtained every 15 minutes during daytime and every 30 minutes during nighttime. Subjects recorded a journal of the activities performed and the time of retiring to bed, ABPM recordings being divided into ‘awake’ or ‘asleep’ periods based on diary entries and not on predefined time intervals. BP variability was calculated as the standard deviation (SD) of mean blood pressure. Results: The hypertensive patients with previously known subclinical disease (SCOD+) compared with those without it (SCOD–) had significantly higher systolic and diastolic BP after SARS-CoV-2 infection, and significantly increased variability of both systolic and diastolic BP. Also, they had a significantly reduced decrease of nocturnal systolic BP (table 1). The analysis for each marker of subclinical organ damage indicated that increased systolic BP variability in hypertensive COVID-19 patients was significantly correlated with carotid IMT (r = 0.517, p = 0.001), brachial artery FMD (r = 0.426, p = 0.008), LVMI (r = 0.397, p = 0.009), E/e` ratio (r = 0.543, p = 0.001), left atrial volume indexed to BSA (LAVI) (r = 0.478, p = 0.003) and that diastolic BP variability is significantly correlated with carotid IMT (r = 0.362, p = 0.09), brachial artery FMD (r = 0.491, p = 0.006), LVMI (r = 0.369, p = 0.008), E/e` ratio (r = 0.422, p = 0.005), left atrial volume indexed to BSA (LAVI) (r = 0.407, p = 0.002). Conclusions: Our study indicates that SARS-CoV-2 infection in hypertensive patients induces an increased blood pressure variability which is significantly correlated with the presence of previously diagnosed subclinical disease.

Potential variables forcing litterfall in a lower montane evergreen forest using Granger and superposed epoch analyses

AbstractThe interplay between long‐term environmental variability and litterfall is complex and through this study, we quantified the response of peak leaf, flower, and fruit litterfall production to such variability in a lower montane evergreen forest located in Doi Suthep‐Pui National Park, Thailand. We observed seasonality in litterfall accumulation with peak leaf and flower litterfalls occurring mostly during the cool and hot dry seasons, while fruit litterfall occurs mostly during the wet season. Probable associations with environmental drivers (barometric pressure, temperature, relative humidity, number of sunlight hours, evaporation, wind speed, and vapor pressure deficit) were tested on a 5‐year litter trap dataset using superposed epoch analysis and Granger causality tests. The tests indicated that significant deviations in barometric pressure, maximum temperature, maximum relative humidity, and wind speed were the most plausible precursors to peak litter production of all components. Additionally, we observed a lag in peak litterfall production relative to climate variability by up to 4 months for most of the climate variables. Changing environmental conditions can affect both the timing and amount of litterfall production, which in turn can alter the nutrient recycling rate and other essential ecosystem services of such forests.

Analysis of Association of Brain Natriuretic Peptide Levels and Blood Pressure Variability

Objective: The present study aimed to investigate the relationship between brain natriuretic peptide (BNP) levels and blood pressure variability among hypertensive patients aged over 40 years.
 Methods: The study recruited 120 patients from a cardiology outpatient clinic who had been diagnosed with hypertension and taking antihypertensive medication for at least 6 months. Demographic and clinical information, blood pressure measurements, and blood samples were collected to measure BNP levels. The standard deviation of the mean arterial pressure over 24 hours was calculated as a measure of blood pressure variability. Linear regression was used to examine the association between BNP levels and blood pressure variability while controlling for age, sex, BMI, and medication history.
 Results: The study found a significant positive association between BNP levels and blood pressure variability (β=0.31, p=0.002), even after controlling for other variables. The linear regression model explained 20% of the variance in blood pressure variability (R2=0.20, F=9.52, p<0.001).
 Conclusion: The findings suggest that higher BNP levels are associated with increased blood pressure variability among hypertensive patients. Further studies are needed to explore the underlying mechanisms and the potential implications of this association.

Thermodynamic modeling for ternary clathrate hydrates of carbon dioxide, nitrogen and tetrahydrofuran

Hydrate-based CO2 separation technology is one of research hotspots in the field of Carbon Capture, Utilization, and Storage. However, thermodynamics, such as phase temperature and pressure, are very important for CO2 separation. In this study, a thermodynamic model was developed for calculating the temperature, pressure, separation efficiency and separation factor of the CO2-N2-THF/H2O system at the three-phase equilibrium of vapor–liquid-hydrates (V-L-H). The Chen-guo model was applied for the hydrate phase and the Patel-Teja equation of state (EOS) was used for the vapor phase. The Wilson activity coefficient model was employed for the liquid phase and the solubility of CO2 in solution was calculated using Henry's law. The average absolute deviation of the equilibrium pressure and temperature compared to the experimental data are 10.441% and 0.343%, respectively, which showed that the predicted three-phase equilibrium pressure and temperature were in good agreement with the experimental results. The three-phase equilibrium temperature and pressure of CO2 and N2 gas mixture in pure water and in THF aqueous solutions were compared. The results showed that THF had a promotion effect in reducing temperature and pressure of CO2 hydrate formation.

ASU model with multiple adjustment types for oxygen scheduling concerning pipe pressure safety in steel enterprises

Steel production requires enough oxygen, which is produced by cryogenic air separation (ASU) with a large load, high power, and slow adjustment. Facing complex oxygen demands, effective ASU scheduling can reduce energy waste and has great potential for low-carbon development. Current ASU scheduling models have only a sole load-adjustment type. To address the limitation, a novel scheduling framework model is researched for ASUs with various load-adjustment types, and is applied to an oxygen system scheduling mode1 for steel enterprises. In addition, current multi-period oxygen scheduling models have an issue that time discretization leads to oxygen pipe pressure deviation between model calculation and practical operation and impacts on system safety. Therefore, a novel method to compensate for pressure boundaries is studied to precisely handle the deviation. Some contrast tests concerning various load-adjustment types of ASU are conducted with simulative and real data. The simulative tests indicate that the framework can both unify multiple adjustment types (MAT) and flexibly migrate among various ASUs. In the real scenario, the oxygen scheduling model with the MAT-ASU avoids oxygen emission and reduces comprehensive cost (including electricity consumption and oxygen release loss) of the manual scheduling by 24%. The MAT enhances the response ability to complicated demands, thereby performing better to optimize the comprehensive cost. Though smaller pipe volume or larger discrete period size increases the pressure deviation, the compensation method perfectly ensures safe system operation.

Agreement Between Tongue-Based Oscillometric and Invasive Blood Pressure in Anesthetized Dogs of Various Weights.

This study aimed to evaluate the agreement between oscillometric blood pressure (OBP) measured from the tongue and invasive blood pressure (IBP) measured from the dorsal pedal artery in anesthetized dogs of various body weights. Forty-five client-owned dogs undergoing general anesthesia for surgery or imaging scan were included; weights ranged from 2.5 to 42.6 kg. Agreement between paired IBP and OBP during normotension was verified with reference standards used in small animals and humans. The data were stratified by body weight (≤5 kg versus >5 kg). In the >5 kg group (n = 29), the bias ± standard deviation for mean (2.1 ± 7.9 mm Hg) and diastolic pressure (-2.7 ± 7.9 mm Hg) exhibited reliability that met human standards (<5 ± 8 mm Hg). However, in the ≤5 kg group (n = 16), the bias ± standard deviation met only veterinary standards (≤10 ± 15 mm Hg) for mean (3.1 ± 10.2 mm Hg) and diastolic pressure (-2.5 ± 12.6 mm Hg). Agreement for systolic pressure did not meet either standard for both groups. This study demonstrates that tongue-based OBP is a close estimate of mean/diastolic blood pressure in anesthetized dogs (>5 kg) during normotension by small-animal and human criteria.

Cross-calibration of atomic pressure sensors and deviation from quantum diffractive collision universality for light particles

The room-temperature, velocity-averaged, total cross section for atom–atom and atom–molecule collisions can be approximated using a universal function depending only on the magnitude of the leading order dispersion coefficient, C 6. This feature of the total cross section together with the universal function for the energy distribution transferred by glancing angle collisions ( (Booth et al 2019 New J. Phys. 21 102001)) can be used to empirically determine the total collision cross section and realize a self-calibrating, vacuum pressure standard. This was previously validated for Rb+N2 and Rb+Rb collisions. However, the post-collision energy distribution is expected to deviate from in the limit of small C 6 and small reduced mass. Here we observe this deviation experimentally by performing a direct cross-species loss rate comparison for Rb+H2 and Li+H2 collisions. We measure a velocity averaged total collision cross section ratio of . Based on an ab initio computation of m3 s−1, we deduce m3 s−1, in agreement with a Rb+H2 ab initio value of . By contrast, fitting the Rb+H2 loss rate as a function of trap depth to the universal function we find m3 s−1. This work demonstrates the utility of sensor-atom cross-calibration experiments to check the validity of theoretical computations to extend and enhance the performance of cold atom based pressure sensors.

Correlation between coefficient of variation of blood pressure and cognitive dysfunction in patients with hypertension complicated by cerebral small vessel disease

ABSTRACT To investigate the correlation between the coefficient of variation of blood pressure and cognitive dysfunction in patients with hypertension complicated by cerebral small vessel disease. 415 patients with hypertension complicated by cerebral small vessel disease who received treatment in our hospital from January 2019 to June 2022 were retrospectively included in this study. These patients were divided into a cognitive dysfunction group (n = 74) and a non-cognitive dysfunction group (n = 341) according to whether they had cognitive dysfunction. Blood pressure and general data were recorded for each patient. The logistic regression coefficient was used to analyze the correlation between coefficient of variation of blood pressure and cognitive dysfunction in patients with hypertension complicated by cerebral small vessel disease. Multivariate logistic regression analysis showed that age, the weighted standard deviation of 24-hour systolic blood pressure (24hSBP-wSD), cholesterol level, and triglyceride level were risk factors for cognitive dysfunction in patients with hypertension complicated by cerebral small vessel disease (P < 0.05). The risk for cognitive dysfunction was increased by 3.532-fold in patients aged>65 years, increased by 1.203-fold in patients with a 24hSBP-wSD of 14.9–15.9%, and increased by 3.033-fold in patients with a 24hSBP-wSD>16.0% (P < 0.05). The coefficient of variation of blood pressure is markedly correlated with the risk for cognitive dysfunction; and a higher coefficient of variation of blood pressure leads to a higher risk for cognitive dysfunction in patients with hypertension complicated by cerebral small vessel disease.

Laser Welding of Fiber and Quartz Glass Ferrule.

Optical fiber sensors fabricated by bonding have several limitations. To address these limitations, a CO2 laser welding process for an optical fiber and quartz glass ferrule is proposed in this study. A deep penetration welding method with optimal penetration (penetrating the base material only) is presented to weld a workpiece according to the requirements of the optical fiber light transmission, size characteristics of the optical fiber, and the keyhole effect of the deep penetration laser welding. Moreover, the influence of laser action time on the keyhole penetration is studied. Finally, laser welding is performed with a frequency of 24 kHz, power of 60 W, and duty cycle of 80% for 0.9 s. Subsequently, the optical fiber is subjected to out-of-focus annealing (0.83 mm, 20% duty cycle). The results show that deep penetration welding produces a perfect welding spot and has good quality; the hole generated from deep penetration welding has a smooth surface; the fiber can bear a maximum tensile force of 1.766 N. The performance of the optical fiber sensor is stable, and the maximum pressure deviation corresponding to the cavity length fluctuation is about 7.2 Pa. Additionally, the linear correlation coefficient R of the sensor is 0.99998.

Twenty-four-hour ambulatory blood pressure variability and association with ischemic stroke subtypes in the subacute stage.

Blood pressure (BP) variability (BPV) increases the risk of cerebral disease in both hemorrhagic and ischemic strokes. However, whether BPV is associated with different types of ischemic stroke remains unclear. In this study, we explored the relationship between BPV and ischemic stroke subtypes. We enrolled consecutive patients aged 47-95 years with ischemic stroke in the subacute stage. We categorized them into four groups based on their artery atherosclerosis severity, brain magnetic resonance imaging markers, and disease history: large-artery atherosclerosis, branch atheromatous disease, small-vessel disease, and cardioembolic stroke. Twenty-four-hour ambulatory blood pressure monitoring was performed, and the mean systolic blood pressure/diastolic blood pressure, standard deviation, and coefficient of variation were calculated. A multiple logistic regression model and random forest were used to test the relationship between BP and BPV in the different types of ischemic stroke. A total of 286 patients, including 150 men (73.0 ± 12.3 years) and 136 women (77.8 ± 9.6 years) were included in the study. Of these, 86 (30.1%) patients had large-artery atherosclerosis, 76 (26.6%) had branch atheromatous disease, 82 (28.7%) had small-vessel disease, and 42 (14.7%) had cardioembolic stroke. There were statistically significant differences in BPV between subtypes of ischemic stroke in 24-h ambulatory blood pressure monitoring. The random forest model showed that BP and BPV were important features associated with ischemic stroke. Multinomial logistic regression analysis demonstrated that systolic blood pressure levels; systolic blood pressure variability at 24 h, daytime and nighttime; and nighttime diastolic blood pressure were independent risk factors for large-artery atherosclerosis after adjustment for confounders. When compared to branch atheromatous disease and small-vessel disease, nighttime diastolic blood pressure and standard deviation of diastolic blood pressure were significantly associated with patients in the cardioembolic stroke group. However, a similar statistical difference was not seen in patients with large-artery atherosclerosis. The results of this study indicate a discrepancy in blood pressure variability among different ischemic stroke subtypes during the subacute stage. Higher systolic blood pressure and systolic blood pressure variability during the 24 h, daytime, and nighttime, and nighttime diastolic blood pressure were independent predictors for large-artery atherosclerosis stroke. Increased nighttime diastolic BPV was an independent risk factor for cardioembolic stroke.