Pressure Variation Research Articles

Cardiac index-guided therapy to maintain optimised postinduction cardiac index in high-risk patients having major open abdominal surgery: the multicentre randomised iPEGASUS trial

BackgroundIt is unclear whether optimising intraoperative cardiac index can reduce postoperative complications. We tested the hypothesis that maintaining optimised postinduction cardiac index during and for the first 8 h after surgery reduces the incidence of a composite outcome of complications within 28 days after surgery compared with routine care in high-risk patients having elective major open abdominal surgery. MethodsIn three German and two Spanish centres, high-risk patients having elective major open abdominal surgery were randomised to cardiac index-guided therapy to maintain optimised postinduction cardiac index (cardiac index at which pulse pressure variation was <12%) during and for the first 8 h after surgery using intravenous fluids and dobutamine or to routine care. The primary outcome was the incidence of a composite outcome of moderate or severe complications within 28 days after surgery. ResultsWe analysed 318 of 380 enrolled subjects. The composite primary outcome occurred in 84 of 152 subjects (55%) assigned to cardiac index-guided therapy and in 77 of 166 subjects (46%) assigned to routine care (odds ratio: 1.87, 95% confidence interval: 1.03–3.39, P=0.038). Per-protocol analyses confirmed the results of the primary outcome analysis. ConclusionsMaintaining optimised postinduction cardiac index during and for the first 8 h after surgery did not reduce, and possibly increased, the incidence of a composite outcome of complications within 28 days after surgery compared with routine care in high-risk patients having elective major open abdominal surgery. Clinicians should not strive to maintain optimised postinduction cardiac index during and after surgery in expectation of reducing complications. Clinical trial registrationNCT03021525.

Post-buckling behavior of variable-arc-length elastica pipe conveying fluid including effects of self-weight and pressure variation

This paper investigated the post-buckling behaviors of a variable-arc-length (VAL) elastica pipe caused by internal transporting fluid motion, accounting for the effects of the self-weight and variation of internal fluid pressure. Both weak-form and strong-form formulations of the VAL elastica pipe were developed. The weak-form formulation was derived by the virtual work principle, and later solved using the nonlinear finite element method (FEM). The strong-form formulation was derived using equilibrium of the force and moment equations, the geometrical relationship of the differential pipe segment, and the energy conservation of the transported fluid. Because of the large displacement analysis, the variation in the internal pressure inside the pipe was considered, which was taken into account by energy conservation based on the Bernoulli principle. Then, the set of nonlinear governing first-order differential equations, corresponding to the two-point boundary value problem, was conveniently solved using the shooting optimization method (SOM). The numerical results obtained from the presented FEM and SOM analyses independently verified each other, with good agreement between these two methods. The parametric study considered the effects of gravity load (pipe and fluid self-weights) and internal fluid pressure on the post-buckling characteristics of the VAL pipe. The numerical results showed that without the pipe and internal fluid weights, the transporting fluid exerted an axial compressive force on the pipe, causing post-buckling phenomena. Beyond the critical state, the support rotation and the length of the VAL pipe increased as the internal fluid velocity decreased. Finally, by including the effect of self-weight, the mode exchange of the odd buckling modes (1st and 3rd modes) was found from the load-displacement path.

Experimental study of multiscale dynamic characterization of the gas-solid phase in a disturbing rotary centrifugal air classifier using pressure signal testing and analysis methods

This study investigates the complex dynamic characteristics of the flow field inside a disturbing rotary centrifugal air classifier through experimental analysis. To this end, micro-pressure sensors are employed to measure pressure signals in different spatial regions under various operating conditions. The analysis includes time-frequency characterization, complexity assessment, and multi-scale energy analysis. The time-domain fluctuation characteristics of the air classifier's pressure signal are closely tied to operating parameters, with the most intense pressure fluctuations occurring in the middle and back region of the air classifier. The loaded condition intensifies the fluctuations, with particle presence exacerbating low-frequency pressure variations and affecting the cyclone's vortex stability. Additionally, the internal installation of the screen cage structure exhibits maximum complexity and randomness in the internal flow field when Rf = 45 Hz, f = 0.4 kg/s, and β = 0°, showing higher randomness and reflecting fine-scale interactions between gas and particles. Conversely, larger scale characteristics are revealed by DET values in higher detail signal levels. Changes in operational parameters, such as perturbation frequency and feeding time, significantly affect the axial distribution of multi-scale energy in the air classifier, with a greater influence on pressure fluctuation at the macroscopic scale, indicating intensified turbulent behavior between gas and particles. This study reveals the influencing mechanisms of various operating parameters on the multiscale dynamic characteristics and complexity of the flow field inside the rotary centrifugal air classifier.

Precise Modulation of CO2 Sorption in Ti8Ce2-Oxo Clusters: Elucidating Lewis Acidity of the Ce Metal Sites and Structural Flexibility.

Investigating the structure-property correlation in porous materials is a fundamental and consistent focus in various scientific domains, especially within sorption research. Metal oxide clusters with capping ligands, characterized by intrinsic cavities formed through specific solid-state packing, demonstrate significant potential as versatile platforms for sorption investigations due to their precisely tunable atomic structures and inherent long-range order. This study presents a series of Ti8Ce2-oxo clusters with subtle variations in coordinated linkers and explores their sorption behavior. Notably, Ti8Ce2-BA (BA denotes benzoic acid) manifests a distinctive two-step profile during the CO2 adsorption, accompanied by a hysteresis loop. This observation marks a new instance within the metal oxide cluster field. Of intrigue, the presence of unsaturated Ce(IV) sites was found to be correlated with the stepped sorption property. Moreover, the introduction of an electrophilic fluorine atom, positioned ortho or para to the benzoic acid, facilitated precise control over gate pressure and stepped sorption quantities. Advanced in situ techniques systematically unraveled the underlying mechanism behind this unique sorption behavior. The findings elucidate that robust Lewis base-acid interactions are established between the CO2 molecules and Ce ions, consequently altering the conformation of coordinated linkers. Conversely, the F atoms primarily contribute to gate pressure variation by influencing the Lewis acidity of the Ce sites. This research advances the understanding in fabricating metal-oxo clusters with structural flexibility and provides profound insights into their host-guest interaction motifs. These insights hold substantial promise across diverse fields and offer valuable guidance for future adsorbent designs grounded in fundamental theories of structure-property relationships.

Thermal and magnetic field structure of near-equatorial coronal holes

Coronal holes are low-density and unipolar magnetic field structures in the solar corona that trigger geomagnetic disturbances on the Earth. Hence, it is important to understand the genesis and evolutionary behavior of these coronal activity features during their passage across the solar disk. We study the day-to-day latitudinal variations of thermal and magnetic field structures of near-equatorial coronal holes. For this purpose, eight years of full-disk SOHO/EIT 195 calibrated images were used. Using the response curves of the SOHO/EIT channels and assuming thermodynamic equilibrium, we estimated the temperature structure of coronal holes. From the latitudinal variation in the magnetic pressure, we inferred the magnitude of the magnetic field structure of coronal holes. Except for the temperature T, we find that the variations in the average photon flux F, in the radiative energy E, in the area A, and in the magnitude of the magnetic field structure B of coronal holes depend on latitude. The typical average values of the estimated physical parameters are $A cm^ $, $F $, $E sec^ $, $T K$ and $ B 0.001) \, G$. When coronal holes are anchored in the convection zone, these activity features would be expected to rotate differentially. The thermal wind balance and isorotation of coronal holes with the solar plasma therefore implies a measurable temperature difference between the equator and the two poles. Contrary to this fact, the variation in the thermal structure of near-equatorial coronal holes is independent of latitude, which leads to the conclusion that coronal holes must rotate rigidly and are likely to be initially anchored below the tachocline. This confirms our previous study.

Research on bearing capacity and stability of deep-water novel combined wellhead based on experimental methods

The combined wellhead has the advantage of high bearing capacity and broad prospects for application in the construction of deep water surface wells; therefore, it is important to conduct relevant research to guide the construction of combined wellheads. The aim of this paper is to study the mechanical characteristics of the combined wellhead in the longitudinal direction and establish the method for real-time calculation of the bearing capacity of the combined wellhead taking into account the effects of installation. The variations of external wall pressure and internal soil pressure during installation and the waiting process of the combined wellhead were investigated by indoor experiments. The installation efficiency of the combined wellhead at different negative pressure conditions was also compared. The experimental results show that the pressure on the outer wall of the combined wellhead facility gradually increases as the depth of the combined wellhead facility increases, and the closer it is to the bottom, the greater the soil pressure. The pressure on the inner soil will increase rapidly during the installation process to almost the same level, while the pressure on the outer soil will increase slightly. During the waiting process of the combined wellhead, as the waiting time increases, the soil damaged during the installation process gradually recovers, and the external wall pressure gradually rises. Moreover, the pressure on the outer wall gradually increases, the pressure on the inner soil decreases slightly leveling off within about 24 h. An appropriate increase in suction pressure facilitates the installation of the combined wellhead, and approximately 2.0 L/min is the optimal option for installation. The computational model developed in this paper and the experimental measurements corroborate each other. These combined wellheads significantly improve the stability of deep water soft-soil well construction and provide a theoretical benchmark for developing oil, gas and hydration in deep water.

Measuring flow rate and purity in portable oxygen concentrators

For people with respiratory disorders who need additional oxygen therapy, oxygen concentrators are vital medical equipment. By concentrating oxygen from the ambient air, they function to give the user a greater flow of oxygen-enriched air. The application of lithium zeolite for oxygen concentration in POCs is the most intense part of this work. One kind of zeolite material that may selectively absorb nitrogen from the air to increase oxygen concentration is lithium zeolite. The capacity, effectiveness, and dependability of a POC fitted with lithium zeolite are all examined in this study, along with its overall performance. The findings show that lithium zeolite, which has benefits including high oxygen purity and low energy consumption, is a potential material for use in POCs. The results of this study aid in the creation of POCs for oxygen therapy that are more effective and efficient. This study suggests utilizing an Arduino microcontroller and an HX710B air pressure sensor to measure the oxygen flow rate in a POC. The POC’s oxygen flow channel incorporates the HX710B sensor to monitor pressure variations, which the Arduino uses to translate into flow rate readings. To verify the accuracy and dependability of the system, its performance is assessed under different flow rate scenarios. Lithium zeolites are well-known for having a high selectivity for nitrogen adsorption, which can enhance the concentrator’s oxygen separation process’s effectiveness. Lithium-zeolite-based oxygen concentrators may have a lower environmental effect than standard concentrators.

Hemodynamic changes in the prone position according to fluid loading after anaesthesia induction in patients undergoing lumbar spine surgery: a randomized, assessor-blind, prospective study

Introduction A change from the supine to prone position causes hemodynamic alterations. We aimed to evaluate the effect of fluid preloading in the supine position, the subsequent hemodynamic changes in the prone position and postoperative outcomes. Patients and methods This prospective, assessor-blind, randomized controlled trial was conducted between March and June 2023. Adults scheduled for elective orthopaedic lumbar surgery under general anaesthesia were enrolled. In total, 80 participants were randomly assigned to fluid maintenance (M) or loading (L) groups. Both groups were administered intravenous fluid at a rate of 2 ml/kg/h until surgical incision; Group L was loaded with an additional 5 ml/kg intravenous fluid for 10 min after anaesthesia induction. The primary outcome was incidence of hypotension before surgical incision. Secondary outcomes included differences in the mean blood pressure (mBP), heart rate, pleth variability index (PVi), stroke volume variation (SVV), pulse pressure variation (PPV), stroke volume index and cardiac index before surgical incision between the two groups. Additionally, postoperative complications until postoperative day 2 and postoperative hospital length of stay were investigated. Results Hypotension was prevalent in Group M before surgical incision and could be predicted by a baseline PVi >16. The mBP was significantly higher in Group L immediately after fluid loading. The PVi, SVV and PPV were lower in Group L after fluid loading, with continued differences at 2–3 time points for SVV and PPV. Other outcomes did not differ between the two groups. Conclusion Fluid loading after inducing general anaesthesia could reduce the occurrence of hypotension until surgical incision in patients scheduled for surgery in the prone position. Additionally, hypotension could be predicted in patients with a baseline PVi >16. Therefore, intravenous fluid loading is strongly recommended in patients with high baseline PVi to prevent hypotension after anaesthesia induction and in the prone position. Trial number KCT0008294 (date of registration: 16 March 2023)

#782 Latent profiles of patients undergoing maintenance hemodialysis based on hemodynamic indicators

Abstract Background and Aims Both intradialytic hypotension and intradialytic hypertension are conditions occurring frequently during hemodialysis and are associated with unfavorable clinical outcomes. However, they remain incompletely understood and poorly defined in the literature. Since intradialytic parameters are now captured automatically in electronic medical records in many institutions, machine learning could emerge as an innovative tool for hemodialysis clinical research. Latent Profile Analysis is a model-based clustering method. It allows to identify hidden subpopulations derived from a set of observed indicator variables, maximizing between-group differences and within-group similarities. Method The objectives of this study were to identify latent profiles using a set of hand-crafted indicators and to interpret these subgroups of patients in a clinically meaningful manner. We conducted a retrospective single-center cohort study of adult patients receiving hemodialysis between January 2017 and December 2022 in Montreal. Given the highly heterogeneous nature of this population, we only enrolled incidental patients. The data were extracted from the NephroCare database, which is the clinical information system used by dialysis teams in our center. Sixteen indicators were derived from time series of blood pressure and heart rate measurements, capturing various patient-centric aspects of intradialytic hemodynamics, including trends, zeniths, nadirs, and time-related features. Latent Profile Analysis involved fitting a series of models, and the best model was selected based on fit indices, evaluation metrics, and clinical interpretation of the distribution of indicator within identified profiles. The primary analysis used complete-case data, and a sensitivity analysis assessed the impact of missing data through multiple imputation. Internal model validation was conducted using k-fold cross-validation. Results The selected model consisted of four profiles with varying variance and null covariance across indicators. Fig. 1 presents radar plots summarizing the identified profiles. Profile 1 included patients with prolonged early nadirs and a nadir-to-zenith transition pattern at the session level. Profile 2 was characterized by frequent nadirs and zeniths without a specific timing preference. Profile 3 comprised patients with infrequent blood pressure variations altogether. Profile 4 included patients with frequent early nadirs but no zeniths. The model demonstrated good generalization to unseen cases and exhibited relative robustness to missing data. Conclusion In this preliminary study, we demonstrated that Latent Profile Analysis can identify clinically meaningful subpopulations of hemodialysis patients based on hemodynamic indicators. The association between the identified profiles and hard clinical endpoints remains to be established.

#2175 Sodium-glucose cotransporter 2 (SGLT2) inhibitors-induced erythropoiesis and cardiovascular events in chronic kidney patients

Abstract Background and Aims Prior research has established that in chronic kidney disease (CKD), elevating hemoglobin (Hb) levels above 11.5 g/dl correlates with heightened thromboembolic event risks and increased mortality. Similar findings are seen in heart failure patients with Hb levels exceeding 13 g/dl, following treatment with erythropoiesis-stimulating agents. Sodium-glucose cotransporter 2 (SGLT2) inhibitors consistently raise Hb levels in CKD patients, both anemic and non-anemic. This study aims to evaluate the consequences of Hb level elevation due to SGLT2 inhibitors beyond the safe threshold in CKD patients and to investigate its association with cardiovascular (CV) events. Method A retrospective observational study was conducted from January 2016 to December 2021, focusing on CKD patients treated with SGLT2 inhibitors. Patients receiving erythropoiesis-stimulating agents or undergoing renal replacement therapy were excluded. We assessed the impact of Hb level changes on atheroembolic events, blood pressure variations, and mortality, while considering demographic data, red blood cell parameters, and renal function indicators. Patients receiving iron treatment were excluded to ensure accurate ferrokinetic parameter assessment. Results The study included 79 CKD patients, predominantly male (76%) and primarily with type 2 diabetes mellitus (T2DM) as the CKD cause (67%). Average follow-up post-SGLT2 inhibitor initiation was 3.5 years (SD 1.4, 0.7-6.7 years). Hb levels increased mainly in the first six months of treatment, with an average increase of 0.7 g/dl/year from baseline (p &amp;lt; 0.01). Ferritin levels slightly decreased (p 0.002), while the transferrin saturation index remained stable. Baseline estimated glomerular filtration rate (eGFR) did not influence Hb increase. Various responses to SGLT2 inhibitors were noted based on baseline Hb levels. No significant association was found between elevated Hb levels (&amp;gt;16.0 g/dl) and increased atheroembolic events, mortality, or blood pressure changes. However, patients with Hb levels &amp;gt;13.0 g/dl experienced more CV events compared to those maintaining Hb ≤13.0 g/dl, though not statistically significant (0% vs 17.5%: p 0.30). Conclusion SGLT2 inhibitor treatment led to a significant Hb increase unless baseline levels were above 16.0 g/dl. Importantly, elevating Hb levels above 13.0 g/dl appears to be linked with a higher incidence of cardiovascular (CV) events, suggesting a potential risk associated with such an increase in Hb levels in this patient population. This finding underscores the necessity for further research to confirm this correlation and to delineate the safe therapeutic window for Hb levels in CKD patients treated with SGLT2 inhibitors.

Use of stepwise lung recruitment maneuver to predict fluid responsiveness under lung protective ventilation in the operating room

Recent research has revealed that hemodynamic changes caused by lung recruitment maneuvers (LRM) with continuous positive airway pressure can be used to identify fluid responders. We investigated the usefulness of stepwise LRM with increasing positive end-expiratory pressure and constant driving pressure for predicting fluid responsiveness in patients under lung protective ventilation (LPV). Forty-one patients under LPV were enrolled when PPV values were in a priori considered gray zone (4% to 17%). The FloTrac-Vigileo device measured stroke volume variation (SVV) and stroke volume (SV), while the patient monitor measured pulse pressure variation (PPV) before and at the end of stepwise LRM and before and 5 min after fluid challenge (6 ml/kg). Fluid responsiveness was defined as a ≥ 15% increase in the SV or SV index. Seventeen were fluid responders. The areas under the curve for the augmented values of PPV and SVV, as well as the decrease in SV by stepwise LRM to identify fluid responders, were 0.76 (95% confidence interval, 0.61–0.88), 0.78 (0.62–0.89), and 0.69 (0.53–0.82), respectively. The optimal cut-offs for the augmented values of PPV and SVV were > 18% and > 13%, respectively. Stepwise LRM -generated augmented PPV and SVV predicted fluid responsiveness under LPV.

Comparison of KNN and LSTM on the Prediction of the Operational Conditions of Natural Gas Pipeline Transmission Networks

During the gas distribution process, a sequence of compressors creates a pressure difference, causing gas to move from regions of high pressure to areas with comparatively lower pressure. The Natural Gas transmission process experiences variations in pressure and temperature, primarily caused by frictional losses, differences in altitude, gas velocity, and the Joule-Thompson effect. Additionally, effective heat transfer to or from the environment contributes to temperature changes throughout the pipeline. The presence of liquid and density changes (hydrate) within the channel also has an impact on the pressure, influencing both pressure and temperature conditions.. This study implements the KNN and LSTM models to predict pressure conditions in natural gas transmission pipelines to analyze the performance comparison of the best model performance using several appropriate parameters to support maximum method performance results. The results show that the LSTM model is better at predicting pressure conditions in natural gas pipeline transmission networks, with an R2 score of 99.45, compared to the KNN model, with an R2 score of 92.82. This study also obtained prediction results from the KNN and LSTM models; the KNN model tends to produce the same pressure value for eight months, while the LSTM model produces pressure values that tend to vary.

First‐Principles Investigations of Structural, Electronic, and Elastic Properties of ZrSiO3 Perovskite: Layer Dependence, Surface Termination, and Pressure Effects

Zirconium silicate (ZrSiO3) perovskite is a promising material for various technological applications. The structural, electronic, and thermodynamic properties of ZrSiO3 perovskite are studied under different conditions, including pressure and layer configuration variations using density functional theory. The present investigation includes a thorough analysis of 2D perovskite derivatives derived from its basic 3D structure. The bulk and surface‐terminated silicon‐dominant SiO2 and zirconium‐dominant ZrO compounds are found to be mechanically stable with an anisotropy factor above 1. The calculated indirect‐bandgap values for the ZrO termination and SiO2 termination are found to be 2.585 and 1.639 eV, respectively. Moreover, the pore size of the SiO2‐terminated slab model of ZrSiO3 is calculated to be 105.39 μm and that for ZrO‐termination to be 129.30 μm. Thus, the material considered for the study can have potential applications in bone regeneration and tissue engineering. Further, the possibilities for modifying ZrSiO3 for uses in electrical devices, sensors, sustainable energy materials, and even biomedical applications like tissue engineering are intriguingly expanded by the present findings.

Coupled variation of pressure and temperature for methane adsorption in coal seam under three initial pressures

Coupled variation of pressure and temperature for methane adsorption in coal seam under three initial pressures

Catalytic hydropyrolysis of cashew de-oiled shell using Py-GC/MS

The present study delves into the impact of different metal oxides (Al2O3, Nb2O5, CaO, CeO2, and ZrO2) and temperatures (350, 450, and 550℃) on the flash pyrolysis of cashew de-oiled shell. Upon analysis using Pyrolysis Gas Chromatography and Mass Spectrometry (Py-GC/MS), the resulting functionalities, including carbonyls, furans, phenolics, hydrocarbons, sugars, and N-containing compounds, have been identified. Additionally, the potential of flash hydro-pyrolysis to upgrade pyrolysis vapors into fuel-grade hydrocarbons has also been studied. The study investigates the effect of hydrogen pressure variations (1, 5, and 10 bar) and the catalytic activity of metal oxides on hydropyrolysis. Characterization of the metal oxides through BET, XRD, SEM, and TPD reveals distinct properties. Notably, incorporating Al2O3 significantly enhances the production of aliphatic hydrocarbons, reaching 78.4 area% at 10 bar of hydrogen. This research advances our understanding of flash pyrolysis and provides insights into sustainable fuel production through targeted catalytic processes.

Production Forecasting at Natural Gas Wells

In Romania, natural gas production is concentrated in two large producers, OMV Petrom and Romgaz. However, there are also smaller companies in the natural gas production area. In these companies, the deposits are mostly mature, or new deposits have low production capacity. Thus, the production forecast is very important for the continued existence of these companies. The model is based on the pressure variation in the gas reservoir, and the exponential model with production decline is currently used by gas and oil producers. Following the variation in the production of the gas wells, we found that in many cases, the Gaussian and Hubbert forecast models are more suitable for simulating the production pattern of gas wells. The models used to belong to the category of poorly conditioned models, with little data, usually called gray models. Papers published in this category are based on data collected over a period of time and provide a forecast of the model for the next period. The mathematical method can lead to a very good approximation of the known data, as well as short-term forecasting in the continuation of the time interval, for which we have these data. The neural network method requires more data for the network learning stage. Increasing the number of known variables is conducive to a successful model. Often, we do not have this data, or obtaining it is expensive and uneconomical for short periods of possible exploitation. The network model sometimes captures a fairly local pattern and changing conditions require the model to be remade. The model is not valid for a large category of gas wells. The Hubbert and Gauss models used in the article have a more comprehensive character, including a wide category of gas wells whose behavior as evolutionary stages is similar. The model is adapted according to practical observations by reducing the production growth period; the layout is asymmetric around the production peak; and the production range is reduced. Thus, an attempt is made to replace the exponential model with the Hubbert and Gauss models, which were found to be in good agreement with the production values. These models were completed using the Monte Carlo method and matrix of risk evaluation. A better appreciation of monthly production, which is an important aspect of supply contracts, and cumulative production, which is important for evaluating the utility of the investment, is ensured. In addition, we can determine the risk associated with the realization of production at a certain moment of exploitation, generating a complete picture of the forecast over the entire operating interval. A comparison with production results on a case study confirms the benefits of the forecasting procedure used.

Identification of the Molecular Components of Enhancer-Mediated Gene Expression Variation in Multiple Tissues Regulating Blood Pressure.

Inter-individual variation in blood pressure (BP) arises in part from sequence variants within enhancers modulating the expression of causal genes. We propose that these genes, active in tissues relevant to BP physiology, can be identified from tissue-level epigenomic data and genotypes of BP-phenotyped individuals. We used chromatin accessibility data from the heart, adrenal, kidney, and artery to identify cis-regulatory elements (CREs) in these tissues and estimate the impact of common human single-nucleotide variants within these CREs on gene expression, using machine learning methods. To identify causal genes, we performed a gene-wise association test. We conducted analyses in 2 separate large-scale cohorts: 77 822 individuals from the Genetic Epidemiology Research on Adult Health and Aging and 315 270 individuals from the UK Biobank. We identified 309, 259, 331, and 367 genes (false discovery rate <0.05) for diastolic BP and 191, 184, 204, and 204 genes for systolic BP in the artery, kidney, heart, and adrenal, respectively, in Genetic Epidemiology Research on Adult Health and Aging; 50% to 70% of these genes were replicated in the UK Biobank, significantly higher than the 12% to 15% expected by chance (P<0.0001). These results enabled tissue expression prediction of these 988 to 2875 putative BP genes in individuals of both cohorts to construct an expression polygenic score. This score explained ≈27% of the reported single-nucleotide variant heritability, substantially higher than expected from prior studies. Our work demonstrates the power of tissue-restricted comprehensive CRE analysis, followed by CRE-based expression prediction, for understanding BP regulation in relevant tissues and provides dual-modality supporting evidence, CRE and expression, for the causality genes.

Method to determine instantaneous transient responses in pressurized pipes from transfer functions and state space for evaluation of leak signals

This article addresses the impact of transient pressure anomalies in hydraulic systems, triggered by the opening or closing of valves or pumps, instantly disturbing the line of hydraulic gradient (LGH). This variation in pressure has significant consequences both in hydraulic and structural terms for water networks. Most of the existing techniques to detect transients in water distribution systems use asynchronous methods, generating timeless information that limits the response capacity in critical situations. Therefore, an automatic transient detection system based on the Internet of Things (IoT) is proposed, capable of identifying overpressure or underpressure pulses in soft real-time, activating alarms to facilitate decision-making. This approach helps maintain the safety of the water distribution system and prevent leaks in the network. Furthermore, a model of the transient behavior of pressure and flow is presented by linearizing the water hammer equations from the Laplace transform, thus generating a transfer function that describes the algebraic relationship between the outlet and inlet of the hydraulic system.•The transient analysis of the hydraulic system prototype underscores its high sensitivity to initial conditions, attributed to turbulence. This observation suggests the possible presence of a dynamic strange attractor related to water hammer phenomena in pressure pipes.•The methodology involving transfer functions and state-space models enables the assessment of how leaks impact the transient responses of the system, including the magnitude, duration, and frequency of disturbances generated by them.•The proposed method introduces a dynamic transfer function capable of identifying instantaneous changes over time in terms of flow and pressure.

A heavy-haul train longitudinal-vertical coupled dynamics model and its dynamic behaviour under emergency braking

The heavy-haul train dynamic performance under emergency braking is complex and directly affects the reliability and running safety. To reveal the heavy-haul train dynamic behaviour in emergency braking process on the long downhill segments, a comprehensive heavy-haul train longitudinal-vertical coupled dynamics model (HTLVDM) that considers the air braking system and coupler draft gear system is established in this paper. HTLVDM considers the components of the locomotive and wagon, such as the wheelset, bogie frame, and car body. The coupler force model considers the nonlinear hysteresis characteristic of the coupler draft gear system. The braking delay time and pressure variation of the brake cylinders are taken into the air braking model. In addition, the validity of HTLVDM is verified by published data. Based on the real-world data of the Shuozhou-Huanghua Line and the established model, the HTLVDM's dynamic responses are analysed through numerical simulations. The results indicate that both the brake forces and coupler forces have a significant effect on the wheel-rail dynamic interactions and the dynamic response of the car body in the heavy-haul train.

Development of planar pressure sensors based on SWCNTs and Poly(aniline)

Planar flexible pressure sensors were produced with single-walled carbon nanotubes (SWCNTs) and poly(aniline) (PANI) composite. Both materials have been processed as films from liquid suspension onto poly(ethylene) terephthalate (PET) substrate, using indium tin oxide electrodes as lateral electrodes. In this device geometry, the pressure can be applied uniformly to the sensing material, reducing its cross-sectional area, and thus increasing the electrical resistance. After pressure removal, the resistance recovers the initial value, a reversible process that can be used in cycles to monitor pressure variations in larger areas and ranges. This device presents a more linear response when compared with layered pressure sensors, where the sensitivity is commonly limited by the mechanical failure of the bottom/top electrodes. Therefore, this approach can be adapted to produce low-cost pressure sensors that allow the monitoring of larger pressure values (up to ∼ 2.2 MPa). The sensor also responds to lower pressure values being applied in punctual regions, in this case, the electrical resistance drops because the sensor responds as an equivalent parallel resistance.