Performance Index Research Articles

Design and Kinematics Analysis of Tensioning Integral Robot

In the past two decades, the technology of robots has developed rapidly. With the enrichment of social needs and applications, the functions of robots have become diversified. The tension-integrated robot designed in this paper is based on the British OC Robotics Series II X125 robot for mechanism design. The mathematical model of the tension-integrated robot is derived, and the kinematic simulation is carried out by Adams and Matlab to verify the correctness of the mathematical model, and the kinematic analysis of the tension-integrated robot is carried out. Firstly, the development and research status of tensioning integral robot is briefly summarized. Because the shape of the tensioning integral robot designed in this paper is similar to that of a snake, the development, structural characteristics and research status of the snake robot are summarized. Secondly, according to the application requirements of the tensioned integral robot, the functions and performance indexes of the tensioned integral robot are analyzed, and the overall structure of the tensioned integral robot is designed, including the body structure of the snake robot, the driving mechanism and the base. The serpentine arm of the serpentine robot is a serpentine structure with twelve joints connected in series. Finally, the mathematical model of the snake robot is derived, and the kinematic simulation of the snake robot is carried out by Adams and Matlab respectively. The obtained image results are the same, which proves that the mathematical model of the snake robot is correctly derived, laying a foundation for further research.

Effect of hamstring flexibility on cervical range of motion and deep neck flexor endurance in healthy young adults: A study to explore myofascial tensegrity network

IntroductionAccording to the concept of biotensegrity, the whole body consists of fascial lines. The relationship between muscles and fascia is important to ensure full and proper range of motion. This study investigated the effect of hamstring flexibility on cervical range of motion and deep neck flexor muscle endurance. The aim was to explore the relationship between the hamstring muscles and neck region in the myofascial tensegrity network. MethodSixty healthy participants with a median age of 22.0 years (24 male, 36 female) were included. Hamstring flexibility was categorized as “normal (n = 31)” or “limited (n = 29)” according to hip flexion angle (HFA) using the passive straight leg raise (PSLR) test. Active cervical range of motion was measured by the Clinometer smartphone application, and the following movements were recorded: flexion, extension and lateral flexion. The craniocervical flexion test was performed to evaluate deep neck flexor endurance using performance index and highest-pressure score. The Mann-Whitney U test was used for statistical analysis. ResultsNo significant differences in cervical range of motion were observed between the groups (p > 0.05). Participants with limited hamstring flexibility presented lower deep neck flexor muscle endurance scores (performance index and highest-pressure score) than participants with normal hamstring flexibility (p = 0.002, and p = 0.012, respectively). ConclusionThe results suggest that hamstring flexibility can influence deep neck flexor muscle endurance in healthy young adults. This preliminary clinical finding supports the hypothesis of a myofascial network between the hamstring muscles and neck region.

Metadata and feature importance analyses of membrane capacitive deionization models: Is a water treatment artificial intelligence panacea possible?

Membrane capacitive deionization (MCDI) is an emerging technology for water purification and desalination. Artificial intelligence (AI) techniques using machine learning (ML) and deep learning (DL) have been widely applied to overcome the drawbacks of conventional numerical models in predicting effluent concentrations, an important parameter to estimate the energy consumption and degree of desalination of the MCDI process. However, despite the remarkable progress of these ML/DL models, relevant studies have only been conducted with limited datasets, leading to a substantial controversy regarding model accuracy. Therefore, in this study, we comprehensively evaluated the performances and applicability of multiple ML/DL models for MCDI using metadata (i.e., performance indices) and feature importance analyses. One MCDI dataset containing both constant-current and constant-voltage operations was reconfigured uniformly or unevenly depending on operation modes. Subsequently, six ML models and one DL model were used to execute the analyses using performance indices. Collectively, this study suggests that a perfect ML/DL model for the water treatment process may not exist, and understanding data types is as important as selecting appropriate models to build a data-driven AI model when process performance is greatly affected by specific input variables (i.e., current and voltage).

The efficiency of chlorophyll fluorescence as a selection criterion for salinity and climate aridity tolerance in barley genotypes.

In the Near East and North Africa (NENA) region, crop production is being affected by various abiotic factors, including freshwater scarcity, climate, and soil salinity. As a result, farmers in this region are in search of salt-tolerant crops that can thrive in these harsh environments, using poor-quality groundwater. The main staple food crop for most of the countries in this region, Tunisia included, is barley. The present study was designed to investigate the sensitivity and tolerance of six distinct barley genotypes to aridity and salinity stresses in five different natural field environments by measuring their photosynthetic activity. The results revealed that tolerant genotypes were significantly less affected by these stress factors than sensitive genotypes. The genotypes that were more susceptible to salinity and aridity stress exhibited a significant decline in their photosynthetic activity. Additionally, the fluorescence yields in growth phases J, I, and P declined significantly in the order of humid environment (BEJ), semi-arid site (KAI), and arid environment (MED) and became more significant when salt stress was added through the use of saline water for irrigation. The stress adversely affected the quantum yield of primary photochemistry (φP0), the quantum yield of electron transport (φE0), and the efficiency by trapped excitation (ψ0) in the vulnerable barley genotypes. Moreover, the performance index (PI) of the photosystem II (PSII) was found to be the most distinguishing parameter among the genotypes tested. The PI of sensitive genotypes was adversely affected by aridity and salinity. The PI of ICARDA20 and Konouz decreased by approximately 18% and 33%, respectively, when irrigated with non-saline water. The reduction was even greater, reaching 39%, for both genotypes when irrigated with saline water. However, tolerant genotypes Souihli and Batini 100/1B were less impacted by these stress factors.The fluorescence study provided insights into the photosynthetic apparatus of barley genotypes under stress. It enabled reliable salinity tolerance screening. Furthermore, the study confirmed that the chlorophyll a fluorescence induction curve had an inflection point (step K) even before the onset of visible signs of stress, indicating physiological disturbances, making chlorophyll fluorescence an effective tool for identifying salinity tolerance in barley.

Optical diffractive neural network imaging through double diffusive mediums

The optical diffractive neural network (ODNN) offers the benefits of high-speed parallelism and low energy consumption. This kind of method holds great potential in the task of reconstructing diffusive images. In this work, we capture a double-scattering dataset by designing optical experiments and use it to evaluate the image reconstruction capability of the constructed ODNNs under more complex scattering scenarios. The Pearson Correlation Coefficient, which is used as a quantitative index of the reconstruction performance, shows that the constructed diffractive networks enable to achieve high performance in the direct recovery of double-scattering data, as well as in the recovery task of stitching images based on two different kinds of double-scattering data. Meanwhile, due to the high redundancy of valid information in the speckle patterns of scattering images, even if parts of the information in the speckle patterns are blocked, the constructed diffractive networks can also show high reconstruction performance without retraining. The capability of the proposed ODNN to reconstruct double-scattering images indicates that the optical diffractive network has the potential to bring transformative applications in more complex scattering scenarios.

Integrated structural and energy building retrofit by reinforced concrete wall addition

In light of the paramount considerations of environmental sustainability and the protection of both life and property, a significant number of existing reinforced concrete (RC) buildings fall short of meeting contemporary standards in terms of their structural and energy performances. In response to these pressing concerns, there is an imperative need for comprehensive building retrofitting processes that integrate both structural and energy considerations. One such approach, the addition of RC walls, is commonly employed as a structural retrofitting technique. However, its potential to enhance overall building efficiency has been relatively underexplored in previous research. In this study, we focus on a representative RC building and utilize two key performance indices: structural residual life and energy consumption, to comprehensively evaluate the impact of RC wall retrofitting on both structural and energy performance. Our investigation considers retrofitting on both the exterior and interior sides of the building. It is observed that the structural performance exhibits notable improvement with the addition of RC walls on either side, and this improvement becomes even more pronounced when complemented by local retrofits to adjacent beams. While the RC walls added on the interior side have negligible impact on the building energy efficiency, those installed on the exterior side could obviously reduce the energy consumption of the HVAC system by 7.9%. Hence, the outcomes of this study indicate that employing the RC wall retrofitting on the exterior side of the existing building is an efficient way to reach structural and energy performance targets simultaneously.

Basic characterization of three kinds of bio-asphalt and research on the low-temperature performance of bio-asphalt mixtures

Bio-oil is a by-product of waste biomass treatment using high-pressure liquefaction, bio-enzymatic, or high-temperature thermal cracking techniques, and can alleviate the shortage of petroleum asphalt resources. This study investigated the production of bio-oil from selected raw materials, including corn stover, castor oil from castor beans, and epoxy vegetable oil from soybeans for the preparation of bio-asphalt. The properties and mechanisms of modification of the three modified bio-asphalts were explored by assessment of basic physical properties, gel permeation chromatography (GPC), temperature scanning (DSR), and thermogravimetric analysis, as well as Semi-Circular Bending (SCB), low-temperature bending, and fatigue tests. Bio-oil was found to improve the low-temperature cracking resistance of the asphalt mixtures, with the improvement further enhanced by changing the blending amount. The bio-oil was observed to negatively affect the low-temperature fatigue performance of the mixes, and the decrease in the n-value indicated that the bio-oil could make the asphalt mixtures less stress-sensitive under repeated loading, with improved anti-fatigue performance of bio-asphalt mixtures observed when the stress ratio was 0.5. Finally, the low-temperature cracking performance index of the corn stover bio-asphalt mixtures was correlated with the gray entropy. The use of the SCB fracture index was found to be more appropriate when using the semicircular bending test to characterize the low-temperature cracking performance of bio-asphalt mixtures.

Multiobjective optimization of hydrostatic thrust bearing operating with electrorheological lubricant using Taguchi-fuzzy technique

An electrorheological (ER) fluid falls in the category of a smart lubricant. In an ER lubricant, the dielectric microparticles are suspended in an insulating lubricant like silicon oil. The properties of ER fluids change when they encounter an external electric field. In the present study, the ER lubricant is modeled using a continuous Bingham model. The finite element method is utilized to solve the Reynolds equation to compute fluid film pressure and associated performance indices like load-carrying capacity, stiffness, and damping parameters of hydrostatic thrust bearing. In the present study, the influencing variables, that is, recess shapes, compensating elements, and strength of an electric field have been optimized using the fuzzy-based Taguchi optimization technique. The optimal combination of recess shape, compensating element, and electric field is required to enhance the performance of the hydrostatic thrust bearing. The authors attempt to see the interaction of the input variable by the trade-off study graph. A Taguchi fuzzy-based multipurpose optimization was proposed to optimize the performance indices and an optimal combination of compensating elements, recess shape, and electric field has been presented.

A Point-Cluster-Partition Architecture for Weighted Clustering Ensemble

Clustering ensembles can obtain more superior final results by combining multiple different clustering results. The qualities of the points, clusters, and partitions play crucial roles in the consistency of the clustering process. However, existing methods mostly focus on one or two aspects of them, without a comprehensive consideration of the three aspects. This paper proposes a three-level weighted clustering ensemble algorithm namely unified point-cluser-partition algorithm (PCPA). The first step of the PCPA is to generate the adjacency matrix by base clusterings. Then, the central step is to obtain the weighted adjacency matrix by successively weighting three layers, i.e., points, clusters, and partitions. Finally, the consensus clustering is obtained by the average link method. Three performance indexes, namely F, NMI, and ARI, are used to evaluate the accuracy of the proposed method. The experimental results show that: Firstly, as expected, the proposed three-layer weighted clustering ensemble can improve the accuracy of each evaluation index by an average value of 22.07% compared with the direct clustering ensemble without weighting; Secondly, compared with seven other methods, PCPA can achieve better clustering results and the proportion that PCPA ranks first is 28/33.

Cell-free DNA screening for common autosomal trisomies using rolling-circle replication in twin pregnancies.

To evaluate the performance of prenatal screening for common autosomal trisomies in twin pregnancies through the use of rolling-circle replication (RCR)-cfDNA as a first-tier test. Prospective multicenter study. Women who underwent prenatal screening for trisomy (T) 21, 18 and 13 between January 2019 and March 2022 in twin pregnancies were included. Patients were included in two centers. The primary endpoint was the rate of no-call results in women who received prenatal screening for common autosomal trisomies by RCR-cfDNA at the first attempt, compared to that in prospectively collected samples from 16,382 singleton pregnancies. The secondary endpoints were the performance indices of the RCR-cfDNA. 862 twin pregnancies underwent screening for T21, T18 and T13 by RCR-cfDNA testing at 10-33weeks' gestation. The RCR-cfDNA tests provided a no-call result from the first sample obtained from the patients in 107 (0.7%) singleton and 17 (2.0%) twin pregnancies. Multivariable regression analysis demonstrated that significant independent predictors of test failure were twin pregnancy and in vitro fertilization conception. All cases of T21 (n=20/862; 2.3%), T18 (n=4/862; 0.5%) and T13 (n=1/862; 0.1%) were correctly detected by RCR-cfDNA (respectively, 20, 4 and 1 cases). Sensitivity was 100% (95% CI, 83.1%-100%), 100% (95% CI 39.8%-100%) and 100% (95% CI 2.5%-100%) for T21, T18 and T13, respectively, in twin pregnancies. The RCR-cfDNA test appears to have good accuracy with a low rate of no-call results in a cohort of twin pregnancies for the detection of the most frequent autosomal trisomies.

СИНТЕЗ ТИПОВИХ ЦИФРОВИХ АСТАТИЧНИХ РЕГУЛЯТОРІВ ПРОМИСЛОВИХ ЕЛЕКТРОПРИВОДІВ

The paper is devoted to the clarification and generalization of the analytical methodology for the synthesis of typical digital astatic regulators of industrial electric drives, which can be presented in the form of discrete transfer functions in the Z-transformation, according to the given speed quality factor, and the development of recommendations for determining the setting parameters of such regulators. It is proposed to determine the coefficient of the integral component according to the given speed quality factor, and determine the other setting parameters in such a way as to compensate for two (for PID-regulators) or one (for PI-regulators) poles of the discrete transfer function of the control object. The ranges of speed quality factor values for a number of electric drives that are optimal in terms of dynamic performance indexes have been determined. It has been proven that to increase the speed in systems with PI controllers, it is necessary to compensate for the larger of the two poles. References 10, figures 5.

Effects of alpha-lipoic acid on the growth performance and serum biochemical index values of puppies

We investigated the effects of alpha-lipoic acid (α-LA) on the growth performance and health level of puppies. A total of 16 healthy Chinese rural dogs aged 30–45 days were randomly divided into four groups: control group (CG), low-dose group (LDG), middle-dose group (MDG) and high-dose group (HDG). The puppies were fed fresh food supplemented with 0, 0.2, 0.4 and 0.6 g/kg of α-LA, respectively. Average daily feed intake (ADFI), average daily gain (ADG), feed-to-gain ratio (F/G), faecal score, intestinal absorption function and serological indices on days 1, 14 and 28 were determined and analysed. The trial period was 28 days. The following results were obtained: (1) α-LA supplementation at 0.4 and 0.6 g/kg significantly increased the ADFI and ADG of the puppies (P < 0.05) but had no significant effect on the faecal score (P > 0.05); (2) α-LA in the fresh diet significantly increased crude fat (EE) digestibility (P< 0.05) but significantly decreased calcium (Ca) digestibility (P< 0.05), without significant impacts on the digestibility of nutrients such as crude protein (CP) and total phosphorus (P); (3) with increasing α-LA inclusion levels, the content of D-xylose in the blood serum increased, but there was no significant difference among groups (P = 0.097). Adding 0.6 mg/kg α-LA to the fresh diet significantly increased the content of IgG in the serum after 14 and 28 days (P < 0.05). At 28 days, adding 0.4 and 0.6 g/kg α-LA to the fresh diet could significantly increase the contents of albumin (ALB) and total protein (TP) in the blood serum (P < 0.05), and the addition of 0.6 g/kg α-LA could significantly increase the serum levels of IgA and IgG (P < 0.05). The addition of α-LA significantly increased the activities of total antioxidant capacity (T-AOC), glutathione peroxidase (GSH-Px) and total superoxide dismutase (T-SOD) (P < 0.05), decreased the content of malondialdehyde (MDA) (P < 0.05), decreased the levels of interleukin-1β (IL-1β) and interleukin-6 (IL-6) (P< 0.05) and increased the content of interleukin-10 (IL-10) in the blood serum (P < 0.05). In conclusion, the addition of α-LA at 0.6 g/kg to the fresh diet of puppies can improve the ADFI, ADG, serum immune capacity, antioxidant capacity and anti-inflammatory capacity of puppies.

Zero‐sum game‐based H∞ optimal finite‐time prescribed performance control for nonlinear multiagent systems with actuator faults

AbstractThis article proposes an optimal leader‐follower consensus control protocol with finite‐time prescribed performance for nonlinear multiagent systems suffering from the actuator fault based on the zero‐sum game framework. First, to guarantee the specified performance of the system within a finite time frame, a novel error transformation function (ETF) is constructed. The ETF proposed in this paper can adjust the mapping range of error transformation to achieve better error convergence performance, thereby enhancing the flexibility of the controller design. Then, to compensate for the negative impact of actuator fault, an error‐related item is separated from the optimal performance index function to design an online fault estimator, which can obtain a better error estimation accuracy. Furthermore, to lessen the need for difficult‐to‐verify persistent excitation signal in adaptive dynamic programming algorithm, both historical and real‐time data are applied to adjust the updating law of neural network weight. Moreover, it demonstrates that the signals within the closed‐loop system are bounded and the expected finite‐time prescribed performance can be ensured in the presence of faults. Finally, a numerical example of multiple single‐link robots manipulator system is executed to validate the efficacy of the developed scheme.

Robust control strategies applicable to DC–DC converter with reliability assessment: A review

AbstractThis paper provides an overview of various control strategies for DC–DC converters along with a brief discussion on various performance indices for evaluating the reliability of designed controller. DC–DC converters are emerging as the fastest‐growing interfacing devices in the world because of their emergent applications in almost all domains of engineering. Notably, the non‐linear behavior of DC–DC converters offers a perplexing problem in designing a robust controller. A robust controller must ensure proper closed‐loop stability with desired performance and reliable control for output voltage regulation in the event of various possible perturbations. This creates the requirement for practically implementable non‐linear controllers that can effectively overlook the drawbacks of linear controllers. The prominence of this composition is based on the expansion in tuning techniques of proportional‐integral‐derivative controller gain parameters using linear strategies and heading towards non‐linear strategies by reviewing 196 research papers. The modification in non‐linear control strategies in terms of their fundamental features associated with key benefits and limitations are comprehensively reviewed. This study mostly revolves around non‐linear internal model control (IMC) strategies for parameter tuning of IMC‐based controllers for various order of plants with an improved degree of freedom.

Cost optimization and reliability analysis of fault tolerant system with service interruption and reboot

Due to widespread usage in many real time systems, reliability modeling and cost optimization of fault tolerance system have drawn attention of the practitioners. The fault tolerance in these systems can be provided by the support of maintenance and redundant components that help in smooth operation of the system in spite of failure of some active components. This investigation deals with the performance modeling of a fault-tolerant system consisting of a finite number of active (online) and standby components. During the switching from active to standby, the recovery procedure is performed, which may be imperfect. In case of imperfect recovery, the system reboot takes place. The maintenance of all the components is managed by a repairman (server) which is subject to failure. When the server is interrupted for rendering the service, functioning does not get stopped due to the system switch-over from perfect working to working breakdown mode. The system works even when the server is on working vacation and performs repair jobs of the failed components. The machine repair model based on Markovian process is developed to derive the transient probabilities and other performance indices of the fault tolerant system using Laplace transforms and matrix analytical method. Using the direct search strategy and particle swarm optimization, the cost-benefit analysis is done. The optimal design of the control parameters for the fault-tolerant system are presented by framing a cost-effective ratio function. The model is examined computationally by performing the numerical simulation and cost optimization.

Dynamic event-triggered non-fragile filtering for singular Markovian jump systems with packet dropouts

The problem of dynamic event-based non-fragile filtering for discrete-time singular Markovian jump systems is investigated in this paper, considering network-induced delays and packet dropouts. The random packet dropout is described by a Bernoulli-distributed stochastic variable with a known distribution law. To save limited network resources, an improved dynamic event-triggered scheme is proposed. By utilizing the Lyapunov-Krasovskii stability theory, a sufficient criterion is derived to ensure the stochastic admissibility of the resulting filter error system with a desired H∞ performance index. Based on the derived criterion, a co-design algorithm for the non-fragile filter and the dynamic event-triggered scheme is proposed by solving a set of linear matrix inequalities. The effectiveness and advantages of the proposed method are illustrated by two simulation examples.

Distributed l2−l∞ filtering over wireless sensors based on adaptive event triggering

This paper investigates the design problem of a set of distributed filters. These adaptive event-triggered (AET) filters have the [Formula: see text] property and are suitable for sensor networks characterized by random measurement data loss and dynamic topology switching. In a distributed filtering network, each local filter estimates the system’s state not only relying on the node’s individual information but also using information from neighboring nodes in the network topology. The adaptive event triggering condition is determined by the combination of the latest release data of the filter itself, the estimated value of the current moment, and the latest release data of the neighboring nodes. The event triggering mechanism adopts a threshold adaptive adjustment scheme, which dynamically changes the threshold parameter according to the filtering error under the premise of guaranteeing the filter performance, thus maximally saving the network communication resources. Initially, we used a binary sequence to describe the random loss of sensor measurements, and a Markov chain is used to describe the switching of the filtering network topology. Secondly, a Lyapunov function is created to examine the [Formula: see text] performance index of the filtering error system and investigate its mean square exponential stability. Subsequently, the distributed filter is formulated, and its parameters are determined using the linear matrix inequality approach. Ultimately, the validity of the proposed method is substantiated through numerical illustrations.

Contextual operational energy performance indexing of district heating consumers

Energy performance indices are widely used methods for determining and assessing the efficiency of buildings in operation. However, methodologies for indices that compare heat consumption among buildings and at higher temporal granularity than yearly are needed. This makes it possible for consumers to compare themselves to others to encourage them to improve their energy efficiency. For a district heating system, it also provides the district heating company with an overview of consumers’ energy efficiency (and consumers’ efficiency must be comparable). This is critical due to the interconnectedness of district heating systems, as consumers can indirectly have negative impacts on each other’s operations. Having an overview of the efficiency of consumers can provide useful information for the district heating companies to detect unusual consumption and possible faults. This paper therefore has created a framework for the comparison of heat consumption among buildings, by taking into account various contextualities to make comparisons possible. The framework has been tested on a case study, and its capabilities are showcased.

Harnessing THz Technology: Biosensor for Highly Accurate Cervical Cancer Cell Detection via Refractive Index.

In order to rapidly identify various species of cancer cells in the tissues of person, a unique diamond shaped hollow-core photonic crystal fiber (PCF)-formed by optical waveform is developed and computationally studied. In this investigation, we found the most prevalent cancers, such as HeLa-derived cervical carcinoma. Since normal and cancer cells differ in their refractive indices (RIs), other significant optical properties can be assessed using this information. With the use of the finite element method, a computational tool for solving simultaneous equations, the defining characteristics the suggested cancer cell sensor are examined using COMSOL-Multiphysics software. Additionally, strict mesh parts are used to preserve the utmost level of modeling realism. At 2.4 THz, the PCF detector attains a Relative Sensitivity of around 97.51% and 96.29%, Confinement Loss of 6.1 × 10 -09db/m and 4.39 × 10-07db/m with respect to cervical carcinoma cell and cervical normal cell. The straightforward PCF structure provides a wide chance of application using the continuing fabrication technique, based on these conventional values of performance indices. This biosensor utilizes the distinctive refractive characteristics of cancer cells, providing a highly accurate and dependable approach for the early identification of cervical cancer. This has the potential to significantly transform the process of cervical cancer screening. The novel method boosts the ability to detect and identify certain conditions, leading to increased diagnostic capabilities for early treatment and better results for patients.

Association between Doppler assessment and secondary cesarean delivery for intrapartum fetal compromise in small-for-gestational-age fetuses.

To elucidate the association between arterial and venous Doppler ultrasound parameters and the risk of secondary cesarean delivery for intrapartum fetal compromise (IFC) and neonatal acidosis in small-for-gestational-age (SGA) fetuses. This single-center, prospective, blinded, cohort study included singleton pregnancies with an estimated fetal weight (EFW) < 10th centile above 36 gestational weeks. Upon study inclusion, all women underwent Doppler ultrasound, including umbilical artery (UA) pulsatility index (PI), middle cerebral artery (MCA) PI, fetal aortic isthmus (AoI) PI, umbilical vein blood flow (UVBF), and modified myocardial performance index (mod-MPI). Primary outcome was defined as secondary cesarean section due to IFC. In total, 87 SGA pregnancies were included, 16% of which required a cesarean section for IFC. Those fetuses revealed lower UVBF corrected for abdominal circumference (AC) (5.2 (4.5-6.3) vs 7.2 (5.5-8.3), p = 0.001). There was no difference when comparing AoI PI, UA PI, ACM PI, or mod-MPI. No association was found for neonatal acidosis. After multivariate logistic regression, UVBF/AC remained independently associated with cesarean section due to IFC (aOR 0.61 [0.37; 0.91], p = 0.03) and yielded an area under the curve (AUC) of 0.78 (95% CI, 0.67-0.89). A cut-off value set at the 50th centile of UVBF/AC reached a sensitivity of 86% and specificity of 58% for the occurrence of cesarean section due to IFC (OR 8.1; 95% CI, 1.7-37.8, p = 0.003). Low levels of umbilical vein blood flow (UVBF/AC) were associated with an increased risk among SGA fetuses to be delivered by cesarean section for IFC.