First trimester combined screening for fetal aneuploidies enhanced with additional ultrasound markers: an 8-year prospective study

Objectives: To describe our screening population and audit of the performance of first-trimester screening for Down syndrome, based on a combined test, enhanced with additional ultrasound markers, over the whole period of the study. Material and methods: We performed a prospective study from 2009 to 2016, which included 1358 singleton fetuses with a crown-rump length of 45–84 mm. The risk of aneuploidy was calculated using nuchal translucency, fetal heart rate (FHR), and additional markers, such as nasal bone (NB), tricuspid flow (TF) and ductus venosus (DV), combined with maternal serum free β-human chorionic gonadotropin (fβ-hCG) and pregnancy-associated plasma protein-A (PAPP-A). Results: 87% of patients were evaluated using all the additional ultrasound markers and 97% of patients were assessed using at least two markers, in any combination. 70.5% of patients were also evaluated using maternal serum biochemistry. The most common risk calculation used nuchal translucency, FHR, all additional ultrasound markers, fβ-hCG and PAPP-A in 851 (62.7%) of cases. The adjusted risk of trisomy 21 was greater than 1:100 in 65 (4.8%) women. Of these patients, 58 (87.7%) chose to have an invasive test. There were 24 aneuploid fetuses (1.7%); and from these we identified 12 (50%) trisomy 21, 6 (25%) sex chromosome anomalies, with the remainder being triploidy and trisomy 18/13. The combined test detected 11 of the 12 cases as having trisomy 21, with a first trimester detection rate of 91.7%. 39 fetuses (2.8%) had various types of structural anomalies. Conclusions: The combined test enhanced with all additional ultrasound markers did not show any substantial improvement in T21 detection rate, when compared with using only one of the additional markers

Underactive bladder - an underestimated entity

Introduction. The concept of underactive bladder is relatively new. Currently there is no generally accepted definition of this pathology. Diagnosis depends on urodynamic findings, and symptoms are usually rare and intricated with the symptoms of other urinary pathology. Matherials and methods. This review examines the current literature on underactive bladder regarding pathology, definition, diagnosis, current guidelines, and any further potential medical developments. Conclusions. Underactive bladder is a poorly understood pathologic condition. Only since 2002 has there been any consensus regarding the definition. The diagnosis relies only on urodynamics; clinical diagnosis is a challenge even for a consultant; and treatment does not seem to alleviate much of the suffering. This disease remains underrecognized and undertreated. More research is needed to identify less invasive diagnosis tools and treatment for this pathology

Data-Driven Model-Free Sliding Mode and Fuzzy Control with Experimental Validation

The paper presents the combination of the model-free control technique with two popular nonlinear control techniques, sliding mode control and fuzzy control. Two data-driven model-free sliding mode control structures and one data-driven model-free fuzzy control structure are given. The data-driven model-free sliding mode control structures are built upon a model-free intelligent Proportional-Integral (iPI) control system structure, where an augmented control signal is inserted in the iPI control law to deal with the error dynamics in terms of sliding mode control. The data-driven model-free fuzzy control structure is developed by fuzzifying the PI component of the continuous-time iPI control law. The design approaches of the data-driven model-free control algorithms are offered. The data-driven model-free control algorithms are validated as controllers by real-time experiments conducted on 3D crane system laboratory equipment

A LOW-COST APPROACH TO DATA-DRIVEN FUZZY CONTROL OF SERVO SYSTEMS

Servo systems become more and more important in control systems applications in various fields as both separate control systems and actuators. Ensuring very good control system performance using few information on the servo system model (viewed as a controlled process) is a challenging task. Starting with authors’ results on data-driven model-free control, fuzzy control and the indirect model-free tuning of fuzzy controllers, this paper suggests a low-cost approach to the data-driven fuzzy control of servo systems. The data-driven fuzzy control approach consists of six steps: (i) open-loop data-driven system identification to produce the process model from input-output data expressed as the system step response, (ii) Proportional-Integral (PI) controller tuning using the Extended Symmetrical Optimum (ESO) method, (iii) PI controller parameters mapping onto parameters of Takagi-Sugeno PI-fuzzy controller in terms of the modal equivalence principle, (iv) closed-loop data-driven system identification, (v) PI controller tuning using the ESO method, (vi) PI controller parameters mapping onto parameters of Takagi-Sugeno PI-fuzzy controller. The steps (iv), (v) and (vi) are optional. The approach is applied to the position control of a nonlinear servo system. The experimental results obtained on laboratory equipment validate the approach

Performance Improvement of Low-Cost Iterative Learning-Based Fuzzy Control Systems for Tower Crane Systems

This paper is dedicated to the memory of Prof. Ioan Dzitac, one of the fathers of this journal and its founding Editor-in-Chief till 2021. The paper addresses the performance improvement of three Single Input-Single Output (SISO) fuzzy control systems that control separately the positions of interest of tower crane systems, namely the cart position, the arm angular position and the payload position. Three separate low-cost SISO fuzzy controllers are employed in terms of first order discrete-time intelligent Proportional-Integral (PI) controllers with Takagi-Sugeno-Kang Proportional-Derivative (PD) fuzzy terms. Iterative Learning Control (ILC) system structures with PD learning functions are involved in the current iteration SISO ILC structures. Optimization problems are defined in order to tune the parameters of the learning functions. The objective functions are defined as the sums of squared control errors, and they are solved in the iteration domain using the recent metaheuristic Slime Mould Algorithm (SMA). The experimental results prove the performance improvement of the SISO control systems after ten iterations of SMA

A CENTER MANIFOLD THEORY-BASED APPROACH TO THE STABILITY ANALYSIS OF STATE FEEDBACK TAKAGI-SUGENO-KANG FUZZY CONTROL SYSTEMS

The aim of this paper is to propose a stability analysis approach based on the application of the center manifold theory and applied to state feedback Takagi-Sugeno-Kang fuzzy control systems. The approach is built upon a similar approach developed for Mamdani fuzzy controllers. It starts with a linearized mathematical model of the process that is accepted to belong to the family of single input second-order nonlinear systems which are linear with respect to the control signal. In addition, smooth right-hand terms of the state-space equations that model the processes are assumed. The paper includes the validation of the approach by application to stable state feedback Takagi-Sugeno-Kang fuzzy control system for the position control of an electro-hydraulic servo-system

Underactive bladder - an underestimated entity

Introduction. The concept of underactive bladder is relatively new. Currently there is no generally accepted definition of this pathology. Diagnosis depends on urodynamic findings, and symptoms are usually rare and intricated with the symptoms of other urinary pathology. Matherials and methods. This review examines the current literature on underactive bladder regarding pathology, definition, diagnosis, current guidelines, and any further potential medical developments. Conclusions. Underactive bladder is a poorly understood pathologic condition. Only since 2002 has there been any consensus regarding the definition. The diagnosis relies only on urodynamics; clinical diagnosis is a challenge even for a consultant; and treatment does not seem to alleviate much of the suffering. This disease remains underrecognized and undertreated. More research is needed to identify less invasive diagnosis tools and treatment for this pathology

Proportional-Integral-Derivative Gain-Scheduling Control of a Magnetic Levitation System

The paper presents a gain-scheduling control design procedure for classical Proportional-Integral-Derivative controllers (PID-GS-C) for positioning system. The method is applied to a Magnetic Levitation System with Two Electromagnets (MLS2EM) laboratory equipment, which allows several experimental verifications of the proposed solution. The nonlinear model of MLS2EM is linearized at seven operating points. A state feedback control structure is first designed to stabilize the process. PID control and PID-GS-C structures are next designed to ensure zero steady-state control error and bumpless switching between PID controllers for the linearized models. Real-time experimental results are presented for validation.

Characterization of sepsis inflammatory endotypes using circulatory proteins in patients with severe infection:a prospective cohort study

Background Sepsis is a heterogeneous syndrome due to a variable range of dysregulated processes in the host immune response. Efforts are made to stratify patients for personalized immune-based treatments and better prognostic prediction. Using gene expression data, different inflammatory profiles have been identified. However, it remains unknown whether these endotypes mirror inflammatory proteome profiling, which would be more feasible to assess in clinical practice. We aim to identify different inflammatory endotypes based on circulating proteins in a cohort of moderately ill patients with severe infection (Sepsis-2 criteria). Methods In this prospective study, 92 inflammatory plasma markers were profiled using a targeted proteome platform and compared between patients with severe infection (Sepsis-2 criteria) and healthy controls. To identify endotypes with different inflammatory profiles, we performed hierarchical clustering of patients based on the differentially expressed proteins, followed by clinical and demographic characterization of the observed endotypes. Results In a cohort of 167 patients with severe infection and 192 healthy individuals, we found 62 differentially expressed proteins. Inflammatory proteins such as TNFSF14, OSM, CCL23, IL-6, and HGF were upregulated, while TRANCE, DNER and SCF were downregulated in patients. Unsupervised clustering identified two different inflammatory profiles. One endotype showed significantly higher inflammatory protein abundance, and patients with this endotype were older and showed lower lymphocyte counts compared to the low inflammatory endotype. Conclusions By identifying endotypes based on inflammatory proteins in moderately ill patients with severe infection, our study suggests that inflammatory proteome profiling can be useful for patient stratification