A Computational Analysis for Active Flow and Pressure Control Using Moving Roller Peristalsis

Peristaltic motion arises in many physiological, medical, pharmaceutical and industrial processes. Control of the fluid volume rate and pressure is crucial for pumping applications, such as the infusion of intravenous liquid drugs, blood transportation, etc. In this study, a simulation of peristaltic flow is presented in which occlusion is imposed by pairs of circular rollers that squeeze a deformable channel connected to a reservoir with constant fluid pressure. Naturally, this kind of flow is laminar; hence, the computation occurred in this context. The effect of the number and speed of the pairs of rollers, as well as that of the intrapair roller gap, is investigated. Non-Newtonian fluids are considered, and the effect of the shear-thinning behavior degree is examined. The volumetric flow rate is found to increase with an increase in the number of rollers or in the relative occlusion. A reduction in the Bird–Carreau power index resulted in a small reduction in transport efficiency. The characteristic of the pumping was computed, i.e., the induced pressure as a function of the fluid volume rate. A strong positive correlation exists between relative occlusion and induced pressure. Shear-thinning behavior significantly decreases the developed pressure compared to Newtonian fluids. The immersed boundary method on curvilinear coordinates is adapted and validated for non-Newtonian fluids.

Three-dimensional Shear Wave Elastography Using a 2D Row Column Addressing (RCA) Array

Objective: To develop a 3D shear wave elastography (SWE) technique using a 2D row column addressing (RCA) array, with either external vibration or acoustic radiation force (ARF) as the shear wave source. Impact Statement: The proposed method paves the way for clinical translation of 3D-SWE based on the 2D RCA, providing a low-cost and high volume-rate solution that is compatible with existing clinical systems. Introduction: SWE is an established ultrasound imaging modality that provides a direct and quantitative assessment of tissue stiffness, which is significant for a wide range of clinical applications including cancer and liver fibrosis. SWE requires high frame-rate imaging for robust shear wave tracking. Due to the technical challenges associated with high volume-rate imaging in 3D, current SWE techniques are typically confined to 2D. Advancing SWE from 2D to 3D is significant because of the heterogeneous nature of tissue, which demands 3D imaging for accurate and comprehensive evaluation. Methods: A 3D SWE method using a 2D RCA array was developed with a volume-rate up to 2000 Hz. The performance of the proposed method was systematically evaluated on tissue-mimicking elasticity phantoms. Results: 3D shear wave motion induced by either external vibration or ARF was successfully detected with the proposed method. Robust 3D shear wave speed maps were reconstructed for both homogeneous and heterogeneous phantoms with inclusions. Conclusion: The high volume-rate 3D imaging provided by the 2D RCA array provides a robust and practical solution for 3D SWE with a clear pathway for future clinical translation.

Three-dimensional fluid-driven stable frictional ruptures

We investigate the quasi-static growth of a fluid-driven frictional shear crack that propagates in mixed mode (II+III) on a planar fault interface that separates two identical half-spaces of a three-dimensional solid. The fault interface is characterized by a shear strength equal to the product of a constant friction coefficient and the local effective normal stress. Fluid is injected into the fault interface and two different injection scenarios are considered: injection at constant volume rate and injection at constant pressure. We derive analytical solutions for circular ruptures which occur in the limit of a Poisson's ratio ν=0 and solve numerically for the more general case in which the rupture shape is unknown (ν≠0). For an injection at constant volume rate, the fault slip growth is self-similar. The rupture radius (ν=0) expands as R(t)=λL(t), where L(t) is the nominal position of the fluid pressure front and λ is an amplification factor that is a known function of a unique dimensionless parameter T. The latter is defined as the ratio between the distance to failure under ambient conditions and the strength of the injection. Whenever λ>1, the rupture front outpaces the fluid pressure front. For ν≠0, the rupture shape is quasi-elliptical. The aspect ratio is upper and lower bounded by 1/(1-ν) and (3-ν)/(3-2ν), for the limiting cases of critically stressed faults (λ≫1, T≪1) and marginally pressurized faults (λ≪1, T≫1), respectively. Moreover, the evolution of the rupture area is independent of the Poisson's ratio and grows simply as Aᵣ(t)=4παλ²t, where α is the fault hydraulic diffusivity. For injection at constant pressure, the fault slip growth is not self-similar: the rupture front evolves at large times as ∝(αt)⁽¹⁻ᵀ⁾ᐟ² with T between 0 and 1. The frictional rupture moves at most diffusively (∝√(αt)) when the fault is critically stressed, but in general propagates slower than the fluid pressure front. Yet in some conditions, the rupture front outpaces the fluid pressure front. The latter will eventually catch the former if injection is sustained for a sufficient time. Our findings provide a basic understanding on how stable (aseismic) ruptures propagate in response to fluid injection in 3-D. Notably, since aseismic ruptures driven by injection at constant rate expands proportionally to the squared root of time, seismicity clouds that are commonly interpreted to be controlled by the direct effect of fluid pressure increase might be controlled by the stress transfer of a propagating aseismic rupture instead. We also demonstrate that the aseismic moment M₀ scales to the injected fluid volume V as M₀ ∝ V³ᐟ².

The Influence of Technological Parameters on Morphology of Electrospun Nanofibers Based on Hyaluronic Acid

Electrospinning as a high-functioning, multi-operated, and advanced method of nanofiber production allowing to obtain fibrous materials based on different polymers for a wide range of biomedical and bioengineering applications. Hyaluronic acid is one of the most promising polymers for nanofiber formation due to its unique biological and biochemical properties. In spite of the difficulties and special features of the electrospinning from hyaluronic acid solutions, the amount of studies in this field is ever-growing. Unfortunately, there is a significant shortage of fundamental data describing the relations between the technological parameters and the nanofiber morphology. This study considers the key technological parameters of the electrospinning process such as applied voltage and flow volume rate and evaluates their influence on the morphology, mean diameter, and diameter distribution width of nanofibers based on native hyaluronic acid. The optimal range of the defined parameters has been established, at which the stability of the fiber formation is ensured. It is shown that by varying of the applied voltage and the flow volume rate of the polymer spinning solution, it is possible to control the properties of nanofibers.

Volume Rate Adjustment for Pesticide Applications against Aonidiella aurantii in Citrus: Validation of CitrusVol in the Growers’ Practice

Aonidiella aurantii is one of the most damaging armored scales in citrus crops worldwide. To control this pest, high water volume rates are conventionally used. In order to rationalize the pesticide applications in citrus, IVIA developed CitrusVol, a tool that recommends the optimal volume rate based on the vegetation, the pest or disease and the active ingredient. In this study the objectives were: (i) validate CitrusVol as a tool to adjust the spray volume to control A. aurantii and (ii) quantify its environmental and economical advantages. For this, the spray volume adjusted with CitrusVol was compared with the one conventionally used by farmers in 18 applications in seven orchards during two years. The following parameters were evaluated: (i) spray distribution in the canopy, (ii) A. aurantii males trapped per day, and (iii) number of scales per fruit at harvest. CitrusVol reduced the spray volume and the amount of pesticide by 35% on average. Despite this reduction, a satisfactory spray distribution was achieved, and the volume was found to control the pest in a comparable way to the conventional volume. Moreover, CitrusVol saved per application and on average 31.25 h/100 ha of spray operating time, 241.83 L/100 ha of fuel consumption and consequently, the reduction of emissions of CO2 was 631.18 kg/100 ha. Therefore, CitrusVol allows for efficient, low-input and low-impact pesticide applications.

Decreased renal function increases the nighttime urine volume rate by carryover of salt excretion to the nighttime

To determine the pathophysiology of nocturnal polyuria associated with renal dysfunction, patients who underwent laparoscopic nephrectomy were prospectively studied. The diurnal variation in urine volume, osmolality, and salt excretion were measured on preoperative day 2 and postoperative day 7. The factors associated with an increase in the nighttime urine volume rate with decreased renal function were evaluated using multiple linear regression analysis. Forty-nine patients were included. The estimated glomerular filtration rate decreased from 73.3 ± 2.0 to 47.2 ± 1.6 mL/min/1.73 m2 (P < 0.01) and the nighttime urine volume rate increased from 40.6% ± 2.0% to 45.3% ± 1.5% (P = 0.04) with nephrectomy. The nighttime urine osmolality decreased from 273 ± 15 to 212 ± 10 mOsm/kg and the nighttime salt excretion rate increased from 38.7% ± 2.1% to 48.8% ± 1.7% (both P < 0.01) with nephrectomy. Multiple linear regression analysis showed that the increase in the nighttime urine volume rate was strongly affected by the increase in the nighttime salt excretion rate. A decrease in renal function causes an increase in the nighttime urine volume rate, mainly because of an increase in nighttime salt excretion.Trial registration number: UMIN000036760 (University Hospital Medical Information Network Clinical Trials Registry).Date of registration: From 1 June 2019 to 31 October 2020.

Assessment of Vineyard Canopy Characteristics from Vigour Maps Obtained Using UAV and Satellite Imagery

Canopy characterisation is a key factor for the success and efficiency of the pesticide application process in vineyards. Canopy measurements to determine the optimal volume rate are currently conducted manually, which is time-consuming and limits the adoption of precise methods for volume rate selection. Therefore, automated methods for canopy characterisation must be established using a rapid and reliable technology capable of providing precise information about crop structure. This research providedregression models for obtaining canopy characteristics of vineyards from unmanned aerial vehicle (UAV) and satellite images collected in three significant growth stages. Between 2018 and 2019, a total of 1400 vines were characterised manually and remotely using a UAV and a satellite-based technology. The information collected from the sampled vines was analysed by two different procedures. First, a linear relationship between the manual and remote sensing data was investigated considering every single vine as a data point. Second, the vines were clustered based on three vigour levels in the parcel, and regression models were fitted to the average values of the ground-based and remote sensing-estimated canopy parameters. Remote sensing could detect the changes in canopy characteristics associated with vegetation growth. The combination of normalised differential vegetation index (NDVI) and projected area extracted from the UAV images is correlated with the tree row volume (TRV) when raw point data were used. This relationship was improved and extended to canopy height, width, leaf wall area, and TRV when the data were clustered. Similarly, satellite-based NDVI yielded moderate coefficients of determination for canopy width with raw point data, and for canopy width, height, and TRV when the vines were clustered according to the vigour. The proposed approach should facilitate the estimation of canopy characteristics in each area of a field using a cost-effective, simple, and reliable technology, allowing variable rate application in vineyards.

Decreased renal function increases the nighttime urine volume rate by carryover of salt excretion to the nighttime

Purpose: To determine the pathophysiology of nocturnal polyuria associated with renal dysfunction.Methods: Patients who underwent laparoscopic nephrectomy were studied prospectively. The diurnal variation in urine volume, osmolality, and salt excretion were measured on preoperative day two and postoperative day seven. The factors associated with an increase in the nighttime urine volume rate with decreased renal function were evaluated by multiple linear regression analysis.Results: Forty-nine patients were included. The eGFR decreased from 73.3 ± 2.0 to 47.2 ± 1.6 mL/min/1.73 m2 (P < 0.01) and the nighttime urine volume rate increased from 40.6% ± 2.0% to 45.3% ± 1.5% (P = 0.04) with nephrectomy. The nighttime urine osmolality decreased from 273 ± 15 to 212 ± 10 mOsm/kg (P < 0.01) and the nighttime salt excretion rate increased from 38.7% ± 2.1% to 48.8% ± 1.7% (P < 0.01) with nephrectomy. Multiple linear regression analysis revealed that the increase in the nighttime urine volume rate was strongly affected by the increase in the nighttime salt excretion rate.Conclusion: A decrease in renal function causes an increase in the nighttime urine volume rate, mainly due to an increase in nighttime salt excretion.Trial registration number: UMIN000036760 (University Hospital Medical Information Network Clinical Trials Registry)Date of registration: From June 1st, 2019 to October 31th 2020

Hybrid Artificial Intelligence Methods for Predicting Air Demand in Dam Bottom Outlet

In large infrastructures such as dams, which have a relatively high economic value, ensuring the proper operation of the associated hydraulic facilities in different operating conditions is of utmost importance. To ensure the correct and successful operation of the dam's hydraulic equipment and prevent possible damages, including gates and downstream tunnel, to build laboratory models and perform some tests are essential (the advancement of the smart sensors based on artificial intelligence is essential). One of the causes of damage to dam bottom outlets is cavitation in downstream and between the gates, which can impact on dam facilities, and air aeration can be a solution to improve it. In the present study, six dams in different provinces in Iran has been chosen to evaluate the air entrainment in the downstream tunnel experimentally. Three artificial neural networks (ANN) based machine learning (ML) algorithms are used to model and predict the air aeration in the bottom outlet. The proposed models are trained with genetic algorithms (GA), particle swarm optimization (PSO), i.e., ANN-GA, ANN-PSO, and ANFIS-PSO. Two hydrodynamic variables, namely volume rate and opening percentage of the gate, are used as inputs into all bottom outlet models. The results showed that the most optimal model is ANFIS-PSO to predict the dependent value compared with ANN-GA and ANN-PSO. The importance of the volume rate and opening percentage of the dams' gate parameters is more effective for suitable air aeration.