Flow Measurements Research Articles

High‐Precision Dilatometry for the Study of Precipitation Processes and Microalloying Effects in Lightweight Alloys ‐ A Specific Review

By dilatometry, the absolute change in the length of a sample is measured. As length, i.e., volume, is a state variable, its change can be monitored for long time ranges. This is the decisive advantage compared to the widely applied calorimetric methods which are based on a rate (change of heat) and where the maximum time range is determined by the resolution limit of the heat flow measurement. In contrast, if the measurement environment is kept at a constant temperature, dilatometric signals can be measured for very long time ranges down to very small changes with resolution in the nm range. The application of high‐stability isothermal dilatometry for studying precipitation phenomena in Al(Mg,Si)‐, Ti(V)‐, and Ti(Cr)‐alloys is summarized in the present review. Al(Mg,Si) turns out as a prime example where the various phases can unambiguously be distinguished by their characteristic length change features. For Ti(V), the influence of the oxygen impurity on the omega phase formation, and for Ti(Cr), the effect of Sn alloying on the omega phase formation can be revealed by dilatometry. The results on Al(Mg, Si) are compared with dilatometry on Al(Cu)‐alloys upon time‐linear heating, for which also the effect of microalloying with Au is studied.

Performance study on vacuum suction blasting by force and velocity measurements of the abrasive flow

Performance study on vacuum suction blasting by force and velocity measurements of the abrasive flow

Identification of toll-like receptor 2 as a key regulator of neuronal apoptosis in vascular dementia by bioinformatics analysis and experimental validation

BackgroundVascular dementia (VaD), the second most prevalent type of dementia, lacks a well-defined cause and effective treatment. Our objective was to utilize bioinformatics analysis to discover the fundamental disease-causing genes and pathological mechanisms in individuals diagnosed with VaD. MethodsTo identify potential pathogenic genes associated with VaD, we conducted weighted gene co-expression network analysis (WGCNA), differential expression analysis, and protein–protein interaction (PPI) analysis. The exploration of potential biological mechanisms involved the utilization of Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis. Moreover, a bilateral common carotid artery stenosis (BCAS) mouse model of VaD was established, and the expression of the hub gene, its relationship with cognitive function and its potential pathogenic mechanism were verified by cognitive behavior tests, cerebral blood flow measurement, Western blotting, and immunofluorescence experiments. ResultsThis study identified 293 DEGs from the brain cortex of VaD patients and healthy controls, among these genes, the Toll-like receptor 2 (TLR2) gene was identified as hub gene, and it was associated with the apoptosis-related pathway PI3K/AKT.The BCAS model demonstrated that the use of TLR2 inhibitors greatly enhanced the cognitive function of the mice (p < 0.05). Additionally, there was a notable decrease in the number of apoptotic cells in the brain cortex of the mice (p < 0.01). Moreover, significant alterations in the levels of proteins related to the PI3K/AKT pathway and cleaved-caspase3 proteins were detected (p < 0.05). ConclusionsTLR2 plays a role in the pathophysiology of VaD by enhancing the neuronal apoptotic pathway, suggesting it could be a promising therapeutic target.

Experimental Heat Transfer Analysis of a New Turbulator in a Concentric Heat Exchanger Tube: A Full Factorial Design Approach

Abstract People have been looking for alternative energy sources because current sources may be depleted. Furthermore, it is critical to utilize available energy sources as effectively as possible. Turbulators are among the topics to consider when it comes to energy efficiency. In practice, turbulators are often used in exchangers to enhance heat transfer. Putting newly constructed turbulators in determined locations of the constant surface temperature heat exchanger, velocity, temperatures, pressure, and flow measurements have been performed in the inlet and outlet. In the case of using different numbers of turbulators, their placement in different locations, their arrangement at different distances, and their use at different Reynolds, the changes in pressure drop, Nusselt number, friction factor, efficiency, exergy loss rate, and NTU were determined with the full-factor experimental design. When the test data were evaluated, it was seen that as the number of turbulators increased, the thermal efficiency, friction factor, and pressure loss also increased. Using turbulators in different numbers, at different positions, at different distances, and with different Reynolds numbers, the effect ratio on the pressure loss, Nusselt number, and friction factor parameters was detected. In the analyses made, the most efficient parameters on heat transfer were determined, respectively, as Reynolds number (64.55%), the position of turbulators (19.73%), the distance between turbulators (6.09%), and the number of turbulators (5.94%).

#532 Association between blood flow measured within 30 days from AV access creation and the risk of thrombosis

Abstract Background and Aims The use of arteriovenous (AV) access for hemodialysis (HD) is hampered by the risk of dysfunction and thrombosis. Various factors affect the risk of AV access thrombosis, such as age, female sex, hematocrit, vessels’ diameter and anatomy, and patients’ comorbidities (e.g. diabetes mellitus, thrombophilia, chronic inflammatory disease). Previous studies have reported contradictory results on the prognostic value of intraoperative blood flow (Qa) measurements. Finally, only few studies have investigated the association between postoperative Qa measurements and thrombosis risk. Therefore, current guidelines report that there is not enough evidence to suggest routine assessment of AV access Qa for surveillance. This study aimed to analyze the association between Qa, measured at the first post-operative visit (within 30 days from creation), and thrombosis risk, in distal and proximal autologous AV fistulae (dAVF and pAVF), and AV grafts (AVG). Method This retrospective cohort study included all AV accesses created in San Paolo Hospital (Milan, IT) between January 1st 2013 and December 31st 2022, with a post-operative Qa measurement available within 30 days from the date of creation. AV accesses were classified as dAVF, pAVF and AVG. Qa was measured by ultrasound as the product of the cross-sectional area and the time-averaged mean velocity, in the feeding artery. The thrombosis-free survival of dAVF, pAVF and AVG was plotted using the Kaplan Meier method. The association between Qa and the risk of thrombosis was studied by Cox proportional hazard models, adjusted for patient's age and sex. Non-linearity was assessed using natural splines. Results A total of 218 AV accesses (92 dAVF, 76 pAVF, and 50 AVG) were created in 191 patients. At baseline, patients had a median age of 69 years, 70% were male, 42% were already on HD treatment, and overall, they had a high prevalence of hypertension, diabetes mellitus and cardiovascular comorbidities. At first post-operative visit, median Qa was 922 [698, 1278] ml/min, 1260 [917, 1825] ml/min, and 1665 [1195, 2508] ml/min, respectively for dAVF, pAVF, and AVG (p &amp;lt;0.001). During a median follow up time of 1.35 [0.55, 2.62] years, 66 AV access thrombosis occurred. The thrombosis-free survival rates for dAVF, pAVF and AVG were 84%, 97%, and 51% at 1 year, and 63%, 66%, and 19% at 5 years (Fig. 1). For dAVF we found a significant L-shaped association between Qa measured at the first post-operative visit and thrombosis risk, with the lowest risk found at Qa of 1289 ml/min and an exponential risk increase for dAVF with Qa &amp;lt;800 ml/min (Fig. 2). Particularly, for dAVF with Qa &amp;lt; 1289 ml/min, we found a 39% increased risk of thrombosis for every 100 ml/min decrease in Qa (aHR 1.39, 95% CI 1.10-1.75, p 0.006). In pAVF, Qa showed a trend of inverse linear association with the risk of thrombosis, although not reaching statistical significance (aHR 1.06, 95% CI 0.96-1.17, p 0.24, for every 100 ml/min decrease in Qa). In AVG, Qa was not associated with the risk of thrombosis (aHR 1.01, 95% CI 0.97-1.06, p 0.57, for every 100 ml/min decrease in Qa). Conclusion In our cohort we found that Qa, measured at the first post-operative visit, is associated with the risk of thrombosis in dAVF, but not in pAVF and AVG. In particular, in dAVF the association is non-linear with the lowest risk in our cohort found at Qa equal to 1289 ml/min, with an exponentially increasing risk for Qa &amp;lt;800 ml/min. Our findings suggest that post-operative flow assessment may be a useful tool to identify dAVF at higher risk of thrombosis and allow a closer monitoring or possible preventive interventions.

#957 The immunometabolic profile of human peritoneal macrophages during peritoneal dialysis and its relation to systemic cardiovascular effects

Abstract Background and Aims Patients with end-stage kidney disease (ESKD) treated with peritoneal dialysis (PD) exhibit a high risk of heart failure (HF). This largely concerns HF with a preserved ejection fraction (HFpEF). Uremic toxins, oxidative stress and systemic inflammation related to ESKD contribute to this HFpEF phenotype, which may be aggravated by the daily administration of glucose-rich PD-fluids. These induce insulin resistance and formation of advanced glycaemic end products, resulting in microvascular injury and arteriosclerosis. A hallmark of HFpEF is the presence of profibrotic cardiac macrophages that aggravate fibrosis. In the peritoneum, the non-physiological high glucose concentrations trigger local oxidative stress, fibrosis and inflammation, processes alike those seen in HFpEF. While the role of macrophages in HFpEF is established, the involvement of human peritoneal macrophages (HPMs) in PD-induced peritoneal injury is largely unknown. We hypothesize that HPMs, chronically exposed to the glucose-rich fluids, exhibit an inflammation-driven immunometabolic profile. This may contribute to cardiovascular (CV)-risk in PD-treated patients. We present preliminary results on the isolation of HPMs from PD effluent (PDE) and a detailed protocol to establish the immunometabolic profile of HPMs. These profiles will subsequently be related to cardiac function (left ventricular global longitudinal strain (LV-GLS), an echocardiographic measure of HFpEF) and parameters of systemic inflammation. Method In 15 adult PD-treated patients we will prospectively perform cardiac echography, draw a blood sample and collect PDE for HPM isolation. To obtain control HPMs a peritoneal saline flush will be collected from 5 adult patients with non-metastasized colon cancer during a routine diagnostic laparoscopy. HPMs will be isolated from the PDE and saline by centrifugation, followed by freezing for storage. We compared fresh and thawed cells of a PDE-sample to evaluate the impact of storage on HPM phenotype and functionality, respectively using flow cytometry and measurement of IL-6 production, with and without a lipopolysaccharide (LPS) challenge. In-depth HPM characterization will be performed by measuring glucose and lactate, conducting metabolic flux analysis, assessing glycolysis and mitochondrial characteristics using Seahorse®, and employing cytometry to evaluate reactive oxygen species and metabolic fuel preference. A phenotypical profile will be established using fluorescent probes and antibodies. To assess functionality, HPMs will be exposed in vitro to “M1” and “M2” inducers and we will use human monocyte-derived macrophages from healthy adult controls as a comparison. We will relate the immunometabolic, phenotypical and functional HPM characteristics to LV-GLS, blood cytokine (obtained with Bio-Plex multiplex) and blood immune profiles (obtained with cytometry) in PD-treated patients. Furthermore, we will compare the HPM characteristics of the PD-treated patients with the control group. Results Preliminary results of 6 patients show that we can isolate HPMs from the PDE with a yield of &amp;gt;5M cells. The phenotype and functionality of HPMs was evaluated both directly after isolation and after a freeze-thaw cycle. Flow cytometry showed high percentages of CD14+HLA-DR+CD64+ macrophages in both fresh and biobanked HPMs. IL-6 production was observed in both fresh and biobanked HPMs even without LPS-stimulation (Figure). Conclusion By successfully isolating and storing HPMs from the easily accessible PDE, we optimized the conditions to assess their immunometabolic characteristics. The proposed protocol not only aims to provide valuable insights into HPM phenotype and functionality, but also allows us to relate these to cardiac function and systemic inflammation. With this strategy, we aim to gain insight in the immunometabolic effects of PD on peritoneal immune cells and how these relate to CV-effects.

Data-driven traffic sensor location and path flow estimation using Wasserstein metric

This paper introduces link information value obtained by the traffic sensors and presents a traffic sensor location and flow estimation joint optimization model in an urban road network. In contrast to most previous studies, this paper adds new traffic sensors into the existing sensor network and proposes a data-driven path flow measurement method based on Wasserstein metric, which is utilized to measure the distance between the estimated traffic flow distribution and the actual distribution. Furthermore, this paper develops a customized greedy algorithm by combining a search strategy for the link information value to obtain the optimal sensor location scheme and perform traffic flow estimation under different budget conditions. Numerical experiments are conducted on Sioux-Falls test network and Eastern Massachusetts interstate highway subnetwork to verify the accuracy and effectiveness of the proposed model based on Wasserstein metric and the developed solution method. Computational results show that the sensor location scheme generated by the model based on Wasserstein metric can reduce the estimation error of the traffic flow compared with KL divergence model under the same deployment cost. Additionally, the customized greedy algorithm can achieve the better performance than the Brute force algorithm in terms of computing time and solution quality.

Mitral regurgitation assessment by cardiovascular magnetic resonance imaging during continuous in-scanner exercise: a feasibility study.

Exercise imaging using current modalities can be challenging. This was patient focused study to establish the feasibility and reproducibility of exercise-cardiovascular magnetic resonance imaging (EX-CMR) acquired during continuous in-scanner exercise in asymptomatic patients with primary mitral regurgitation (MR). This was a prospective, feasibility study. Biventricular volumes/function, aortic flow volume, MR volume (MR-Rvol) and regurgitant fraction (MR-RF) were assessed at rest and during low- (Low-EX) and moderate-intensity exercise (Mod-EX) in asymptomatic patients with primary MR. Twenty-five patients completed EX-CMR without complications. Whilst there were no significant changes in the left ventricular (LV) volumes, there was a significant increase in the LVEF (rest 63 ± 5% vs. Mod-EX 68 ± 6%;p = 0.01). There was a significant reduction in the right ventricular (RV) end-systolic volume (rest 68ml(60-75) vs. Mod-EX 46ml(39-59);p < 0.001) and a significant increase in the RV ejection fraction (rest 55 ± 5% vs. Mod-EX 65 ± 8%;p < 0.001). Whilst overall, there were no significant group changes in the MR-Rvol and MR-RF, individual responses were variable, with MR-Rvol increasing by ≥ 15ml in 4(16%) patients and decreasing by ≥ 15ml in 9(36%) of patients. The intra- and inter-observer reproducibility of LV volumes and aortic flow measurements were excellent, including at Mod-EX. EX-CMR is feasible and reproducible in patients with primary MR. During exercise, there is an increase in the LV and RV ejection fraction, reduction in the RV end-systolic volume and a variable response of MR-Rvol and MR-RF. Understanding the individual variability in MR-Rvol and MR-RF during physiological exercise may be clinically important.

Experimental study of simple flumes with converging triangular walls

For water management, the accurate measurement of discharge in irrigation channels is essential. Static flow measuring devices such as weirs and flumes play a significant role in discharge measurement in open channels. Flumes are one of the most commonly used devices for flow measurement. Many researchers have focused on application of simple flumes in irrigation networks. This investigation aims to study the flow discharge through a simple flume with converging triangular walls under free-flow conditions. The flume is constructed by placing two right-angled triangular plates on either side of a rectangular open channel. The channel cross section is rectangular while height of the converging walls reaches to zero at the end of the flume opening. The proposed flume is inexpensive, its operation is simple, its installation is easy and does not require high maintenance (maintenance free). The present study is designed to determine the effect of different variables on flow discharge of this kind of flumes. For this, an experimental program was conducted under upstream subcritical flow regime and under free outflow conditions to formulate the flow discharge of the flume. Flume discharge relationship was deduced using dimensional analysis method and then calibrated using the experimental data collected in this study (318 runs). The proposed discharge equation has an average absolute relative error of 1.66 %, and for 96.5 % of the measured discharge values, the relative errors are within ±5 %. To reliably estimate the flume discharge, free-flow and submerged-flow conditions should be distinguished. For this, suitable equation with an average absolute relative error less than 3.44 % was presented to estimate the submergence threshold. This flume is suitable for the rectangular channel for accurate measurement of free flow at any location on field. This particular device has considerable advantages over the other devices, as it can be quickly installed and removed for use in irrigation channels. The findings and results of this study will be of interest for practical applications.

Assessing Pressure Wave Components for Aortic Stiffness Monitoring through Spectral Regression Learning

Abstract Aims The aging process notably induces structural changes in the arterial system, primarily manifesting as increased aortic stiffness, a precursor to cardiovascular events. While wave separation analysis is a robust tool for decomposing the components of blood pressure waveform, its relationship with cardiovascular events, such as aortic stiffening, is incompletely understood. Furthermore, its applicability has been limited due to the need for concurrent measurements of pressure and flow. Our aim in this study addresses this gap by introducing a spectral regression learning method for pressure-only wave separation analysis. Methods and results Leveraging data from the Framingham Heart Study (2,640 individuals, 55% women), we evaluate the accuracy of pressure-only estimates, their interchangeability with reference method based on ultrasound-derived flow waves, and their association with Carotid-femoral pulse wave velocity. Method-derived estimates are strongly correlated with the reference ones for forward wave amplitude (R2=0.91), backward wave amplitude (R2=0.88), reflection index (R2=0.87), and moderately correlated with time delay between forward and backward waves (R2=0.38). The proposed pressure-only method shows interchangeability with reference method through covariate analysis. Adjusting for age, sex, body size, mean blood pressure, and heart rate, results suggest that both pressure-only and pressure-flow evaluations of wave separation parameters yield similar model performance for predicting Carotid-femoral pulse wave velocity with forward wave amplitude as the only significant factor (p &amp;lt; 0.001; 95% confidence interval, 0.056-0.097). Conclusions We propose an interchangeable pressure-only wave separation analysis method and demonstrate its clinical applicability in capturing aortic stiffening. The proposed method provides valuable non-invasive tool for assessing cardiovascular health.

Design and Realization of Fully Automatic Pump Performance Test System

With the development of automation technology, it gradually replaces manual labor in various fields. Pumps are widely used in various production processes in the industrial field. To enhance the automation level of the pump production and testing process will significantly reduce production costs. This paper aims to design and realize a set of fully automatic, high-precision pump performance testing system. The fully automated operation of the performance test is designed according to the flow rate automatic sampling method, to achieve the accurate measurement of the pump operating conditions. Utilizing the PID algorithm, the valve is automatically adjusted through PLC control to realize the accurate positioning of the flow measurement point. With the help of the software program to carry out the calculation and analysis of test data, to achieve the visualization of the test process of the whole performance test data management. At the same time, SQL Server database is used to realize rapid query and management of test data. After the test verification, the system realizes the full-automatic measurement of the pump performance curve, and the measurement accuracy conforms to the standard of ISO 9906:2012.

Deep Learning-Based Automatic River Flow Estimation Using RADARSAT Imagery

Estimating river flow is a key parameter for effective water resource management, flood risk prevention, and hydroelectric facilities planning. Yet, traditional gauging methods are not reliable under very high flows or extreme events. Hydrometric network stations are often sparse, and their spatial distribution is not optimal. Therefore, many river sections cannot be monitored using traditional flow measurements and observations. In the last few decades, satellite sensors have been considered as complementary observation sources to traditional water level and flow measurements. This kind of approach has provided a way to maintain and expand the hydrometric observation network. Remote sensing data can be used to estimate flow from rating curves that relate instantaneous flow (Q) to channel cross-section geometry (effective width or depth of the water surface). Yet, remote sensing has limitations, notably its dependence on rating curves. Due to their empirical nature, rating curves are limited to specific river sections (reaches) and cannot be applied to other watercourses. Recently, deep-learning techniques have been successfully applied to hydrology. The primary goal of this study is to develop a deep-learning approach for estimating river flow in the Boreal Shield ecozone of Eastern Canada using RADARSAT-1 and -2 imagery and convolutional neural networks (CNN). Data from 39 hydrographic sites in this region were used in modeling. A new CNN architecture was developed to provide a straightforward estimation of the instantaneous river flow rate. Our results yielded a coefficient of determination (R2) and a Nash–Sutcliffe value of 0.91 and a root mean square error of 33 m3/s. Notably, the model performs exceptionally well for rivers wider than 40 m, reflecting its capability to adapt to varied hydrological contexts. These results underscore the potential of integrating advanced satellite imagery with deep learning to enhance hydrological monitoring across vast and remote areas.

Cognition as mediator of pulmonary function and risk of sarcopenia among older adults

BackgroundThe relationship between lung function and sarcopenia remains ambiguous. The primary aim of this study was to investigate the potential association between lung function and sarcopenia in the older adults, as well as to examine the mediating role of cognitive function in this relationship.MethodsThe participants were selected from a nationally representative population-based cohort in China. The peak expiratory flow (PEF) measurement was used to evaluate the lung function in older persons. The sarcopenia was diagnosed using the guidelines of the Asian Working Group for Sarcopenia (AWGS) in 2019. The Cox proportional hazard model was utilized to perform primary analyses of the relationship between PEF and sarcopenia. The mediating effect of cognitive function was evaluated using the counterfactual mediation method.ResultsThis cohort study included 4,011 older adults (average age, 66.6 years; 53.3% males). During a follow-up period of 3.86 years, 349 individuals were diagnosed with sarcopenia. After adjusting for potential confounders, each one-standard-deviation increase in PEF was associated with a 28% reduction in the risk of sarcopenia (hazard ratio [HR]: 0.72; 95% confidence interval [CI]: 0.63, 0.80). There was a significant mediation of cognition for the association between PEF and incident sarcopenia, and the proportion mediated was 12.2% (95% CI: 4.5%, 23.1%).ConclusionsOlder adults with impaired lung function are more likely to develop sarcopenia. Nevertheless, cognition can explain only a small portion of this association. Thus, other potential pathways between lung function and sarcopenia must be elucidated.

Improved Prediction of the Flow in Cylindrical Critical Flow Venturi Nozzles Using a Transitional Model

AbstractCritical flow Venturi nozzles (CFVNs) are a state-of-the-art secondary standard widely used for gas flow measurements with high precision. The flow rate correlates with the type and thickness of the boundary layer (BL) inside the nozzle throat. In the cylindrical type—one of the two standard designs of CFVNs—the nozzle throat encompasses a defined axial length in which the BL develops. This numerical study is concerned with the BL effects in a cylindrical CFVN by means of two turbulence models. Compared to experimental data, the k-$$\omega$$ ω SST model predicts the discharge coefficient well for high and low Reynolds numbers, but not in the intermediate regime. The $$\gamma$$ γ -$$Re_{\theta }$$ R e θ model, on the contrary, agrees well with experimental data in the entire flow range. Relevant quantities and profiles of the BL are separately investigated in the laminar, turbulent, and transitional region. The calculated laminar and turbulent BL thicknesses correspond to predictions based on integral methods for solving the BL equations. Simple representations are proposed for the Zagarola-Smits scaled laminar and turbulent deficit BL profiles removing the effects of axial position, Reynolds number, and pressure gradient. Furthermore, the shape factor is investigated as a characteristic parameter for determining the transitional region.

Development of a Measurement Device for Micro Gas Flowrate Based on Laminar Flow Element with Micro-Curved Surface

The laminar flow meter (LFM) boasts several advantages such as no moving parts, a wide range ratio, high measurement accuracy, quick dynamic response, etc., and is a promising technology for micro gas flow measurement. In order to explore the influence of different curvature radii on curved surface gap LFM, three curved structures with different curvature radii were designed. The computational fluid dynamics method is applied to simulate the flow feature of three structures. The simulated velocity cloud and pressure distribution show that the larger the curvature radius, the more stable the flow of gas medium. The relationship between differential pressure and volume flow was obtained through the test within a flow range of 0~540 sccm. Regression analysis revealed that the volume flow measured by the curved surface LFM had a high linear relationship with the differential pressure. Experimental findings indicate that differential pressure of the structure with a curvature radius of 2 mm was greater than that of other two structures (curvature radius of 6 mm and 3 mm) at the same point. This indicates that adding the number of surfaces can effectively increase the pressure loss, so as to obtain a larger range ratio, but will increase the measurement error.

Weather-dependency of the thermographic flow visualization of the laminar-turbulent transition on wind turbines

Abstract Analyzing the airflow around wind turbines during operation requires an in-process-capable measurement approach that functions without modification of the rotor blade. Infrared–thermographic flow visualization is such a measurement approach. However, its measurement capabilities on wind turbines in operation are highly weather-dependent. Therefore, to understand the expected flow visualization quality in non-laboratory conditions, the dependence of the achievable contrast and contrast-to-noise ratio (CNR) of the laminar-turbulent transition on solar radiation and air temperature is studied, respectively. &amp;#xD;A linear dependence of the contrast on the absorbed solar radiation is derived as a first estimation from a theoretical study of the heat balance. while the air temperature variations are shown to have no effect under certain conditions. The slope of the linear dependence of about 0.025 m2K/W was validated by experiments. To further study the fundamental measurability limit, only the camera noise with constant variance is here applied to determine the achievable contrast-to-noise ratio, which is thus directly proportional to the contrast. &amp;#xD;As a result, the achievable contrast and CNR for visualizing the laminar-turbulent flow transition over the year, over the day, and for different yaw angles of the wind turbine are determined. For this investigation, a wind turbine location near in northern Germany, is assumed as an example, and a maximal achievable contrast and CNR of 4.2 K and 122, respectively, are estimated, which agree with previous measurements. The presented method applies to any other wind turbine location and thus enables planning thermographic flow measurements on any wind turbine in the world.&amp;#xD;

Predicting quadrupole deformation via anisotropic flow and transverse momentum spectra in isotopic 54128-135Xe\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathbf {{}^{128-135}_{\\qquad \\,54}\ extrm{Xe}}$$\\end{document} collisions at LHC

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Cellulose gelation in aqueous hydroxide solutions by CO2(g): Fact and theory

Understanding how the solvent structure affects the stability of the dissolved state and the following precipitation is important for designing future dissolution-coagulation systems for cellulose processing. In this study, two morpholinium hydroxides with different alkyl chain lengths, namely N,N-dimethylmorpholinium hydroxide (NDMMOH(aq)) and N‑butyl‑N-methyl morpholinium hydroxide (BMMorOH(aq)), were studied and compared with the previously thoroughly investigated cellulose solvent benzyltriemethylammonium hydroxide (Triton B(aq)) which is well-known for its superior ability to stabilize the dissolved state. Cellulose solutions in each solvent were characterized by NMR, flow and frequency sweeps, while cellulose coagulation by CO2(g) was followed by in situ FTIR, pH and temperature measurements. The coagulated systems were characterized by CP/MAS 13C NMR, flow, and frequency sweep measurements. Complementary molecular dynamic (MD) simulations were performed to gain a deeper insight into the observed gelation behavior. The intrinsic viscosity indicated more extended cellulose chains in the solvents with more hydrophobic moieties (Triton B and BMMorOH). Even though the course of coagulation did not show any significant differences during monitoring, both the properties of the obtained gels and the MD simulations indicated differences in formation and properties of the coagulated materials that could be related both to the choice of solvent and coagulant.

Aluminium Chloride instead of Ferric chloride for inducing superior sagittal sinus thrombosis to reduce ferromagnetic artifacts on MRI-imaging in experimental models

Using ferric chloride (FeCl3) to induce experimental superior sagittal sinus (SSS) thrombosis might interfere with magnetic resonance imaging (MRI)-assisted visualization and evaluation of the thrombus, the brain parenchyma, and the quality of the occlusion. The aim of this study was to investigate whether aluminum chloride (AlCl3)-induced thrombosis of the SSS has comparable properties to those of FeCl3 without causing artifacts in MRI. SSS thrombosis was induced in 14 male Wistar rats by exposure of the SSS and subsequent topical application of a filter paper strip soaked in AlCl3 (n = 7) or FeCl3 (n = 7) over a period of 15 min. The animals with AlCl3-induced SSS thrombosis showed a constant and complete occlusion with in histological analysis large thrombi. Blood flow measurements indicated a significant reduction on the first and seventh postoperative day compared to preoperative measurements. MRI enabled visualization and subsequent evaluation of the thrombus and the surrounding parenchyma. In comparison, FeCl3-induced SSS thrombosis could not be evaluated by MRI due to artifacts caused by the paramagnetic properties and increased susceptibility of FeCl3. The occluded sinus and the surrounding area appeared hypointense. The quality of SSS occlusion by AlCl3 was comparable to that of FeCl3. AlCl3 therefore represents a significant alternative substance in experimental SSS thrombosis ideally suited for studies using MRI.

Estimation of Suspended Sediment Concentration along the Lower Brazos River Using Satellite Imagery and Machine Learning

This article focuses on developing models that estimate suspended sediment concentrations (SSCs) for the Lower Brazos River, Texas, U.S. Historical samples of SSCs from gauge stations and satellite imagery from Landsat Missions and Sentinel Mission 2 were utilized to develop models to estimate SSCs for the Lower Brazos River. The models used in this study to accomplish this goal include support vector machines (SVMs), artificial neural networks (ANNs), extreme learning machines (ELMs), and exponential relationships. In addition, flow measurements were used to develop rating curves to estimate SSCs for the Brazos River as a baseline comparison of the models that used satellite imagery to estimate SSCs. The models were evaluated using a Taylor Diagram analysis on the test data set developed for the Brazos River data. Fifteen of the models developed using satellite imagery as inputs performed with a coefficient of determination R2 above 0.69, with the three best performing models having an R2 of 0.83 to 0.85. One of the best performing models was then utilized to estimate the SSCs before, during, and after Hurricane Harvey to evaluate the impact of this storm on the sediment dynamics along the Lower Brazos River and the model’s ability to estimate SSCs.