Diversity, geographical distribution and predictive factors of Hepatitis C virus genotypes and subtypes in Rwanda.

Background: Existing data on the prevalence of hepatitis C virus (HCV) genotypes and subtypes in Rwanda need to be strengthened. The aim of this study was to identify HCV genotypes and subtypes among HCV-infected patients, as well as their geographical distribution in Rwanda, and to identify the social and economic factors that could influence HCV epidemiology which would make it possible to target national preventive and management actions for infected patients.

Methods: This study included 560 patients with confirmed chronic HCV infection.

Maternal Streptococcus agalactiae colonization in Europe: data from the multi-center DEVANI study.

Introduction: Despite national guidelines and use of intrapartum antibiotic prophylaxis (IAP), Streptococcus agalactiae (group B streptococci (GBS)) is still a leading cause of morbidity and mortality in newborns in Europe and the United States. The European DEVANI (Design of a Vaccine Against Neonatal Infections) program assessed the neonatal GBS infection burden in Europe, the clinical characteristics of colonized women and microbiological data of GBS strains in colonized women and their infants with early-onset disease (EOD).

Methods: Overall, 1083 pregnant women with a GBS-positive culture result from eight European countries were included in the study.

Malolactic fermentation in lingonberry juice and its use as a preservative.

Lingonberry is a common wild berry that is often sold as jams and beverages. It naturally contains high amounts of the weak acid preservative benzoic acid making it an interesting ingredient for shelf-life extension. Despite this, their use as a raw ingredient is limited by the inherently intense sour taste.

Improved Feedback Quantizer with Discrete Space Vector.

The use of advanced modulation and control schemes for power converters, such as a Feedback Quantizer and Predictive Control, is widely studied in the literature. This work focuses on improving the closed-loop modulation scheme called Feedback Quantizer, which is applied to a three-phase voltage source inverter. This scheme has the natural behavior of mitigating harmonics at low frequencies, which are detrimental to electrical equipment such as transformers.

Occurrence of spp. in Selected Recreational Water Bodies in Belgium during 2021 Bathing Season.

In recent years, a global increase in the number of reports of human vibriosis involving non-O1/O139 (NOVC) and other spp. has been observed. In this context, the Belgian National Reference Center for conducted an assessment of the presence of spp.

Multicenter Performance Evaluation of the Revogene GBS DS Real-Time PCR Assay for Group B Streptococcus Detection During Labor.

Purpose: This study aimed to evaluate the performance and ease of use of the Revogene GBS DS PCR assay for the intrapartum detection of Group B Streptococcus (GBS) colonization, as compared with intrapartum culture and antenatal culture-based screening.

Methods: Between April and August 2019, 398 women who gave birth in one of the three maternities participating in this study agreed to the collection of a vaginal swab when they arrived in the labor ward. The samples were immediately sent to the adjacent laboratory where they were discharged into the buffer provided with the Revogene GBS DS assay.

Multiclass Mask Classification with a New Convolutional Neural Model and Its Real-Time Implementation.

The world has been greatly affected by the COVID-19 pandemic, causing people to remain isolated and decreasing the interaction between people. Accordingly, various measures have been taken to continue with a new normal way of life, which is why there is a need to implement the use of technologies and systems to decrease the spread of the virus. This research proposes a real-time system to identify the region of the face using preprocessing techniques and then classify the people who are using the mask, through a new convolutional neural network (CNN) model.

Architecture Optimization of a Non-Linear Autoregressive Neural Networks for Mackey-Glass Time Series Prediction Using Discrete Mycorrhiza Optimization Algorithm.

Recurrent Neural Networks (RNN) are basically used for applications with time series and sequential data and are currently being used in embedded devices. However, one of their drawbacks is that RNNs have a high computational cost and require the use of a significant amount of memory space. Therefore, computer equipment with a large processing capacity and memory is required.

Neonatal invasive disease caused by Streptococcus agalactiae in Europe: the DEVANI multi-center study.

Purpose: Group B streptococcus (GBS) remains a leading cause of invasive disease, mainly sepsis and meningitis, in infants < 3 months of age and of mortality among neonates. This study, a major component of the European DEVANI project (Design of a Vaccine Against Neonatal Infections) describes clinical and important microbiological characteristics of neonatal GBS diseases. It quantifies the rate of antenatal screening and intrapartum antibiotic prophylaxis among cases and identifies risk factors associated with an adverse outcome.

Interval Type-3 Fuzzy Adaptation of the Bee Colony Optimization Algorithm for Optimal Fuzzy Control of an Autonomous Mobile Robot.

In this study, the first goal is achieving a hybrid approach composed by an Interval Type-3 Fuzzy Logic System (IT3FLS) for the dynamic adaptation of α and β parameters of Bee Colony Optimization (BCO) algorithm. The second goal is, based on BCO, to find the best partition of the membership functions (MFs) of a Fuzzy Controller (FC) for trajectory tracking in an Autonomous Mobile Robot (AMR). A comparative with different types of Fuzzy Systems, such as Fuzzy BCO with Type-1 Fuzzy Logic System (FBCO-T1FLS), Fuzzy BCO with Interval Type-2 Fuzzy Logic System (FBCO-IT2FLS) and Fuzzy BCO with Generalized Type-2 Fuzzy Logic System (FBCO-GT2FLS) is analyzed.

Interval type-3 fuzzy aggregators for ensembles of neural networks in COVID-19 time series prediction.

In this work we are presenting an approach for fuzzy aggregation in ensembles of neural networks for forecasting. The aggregator is used in an ensemble to combine the outputs of the networks forming the ensemble. This is done in such a way that the total output of the ensemble is better than the outputs of the individual modules.

Predictive factors for the presence and long-term persistence of SARS-CoV-2 antibodies in healthcare and university workers.

While patient groups at risk for severe COVID-19 infections are now well identified, the risk factors associated with SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) transmission and immunization are still poorly understood. In a cohort of staff members of a Belgian tertiary academic hospital tested for SARS-CoV-2 antibodies during the early phase of the pandemic and followed-up after 6 weeks, 3 months and 10 months, we collected personal, occupational and medical data, as well as symptoms based on which we constructed a COVID-19 score. Seroprevalence was higher among participants in contact with patients or with COVID-19 confirmed subjects or, to a lesser extent, among those handling respiratory specimens, as well as among participants reporting an immunodeficiency or a previous or active hematological malignancy, and correlated with several symptoms.

FCS-MPC with Nonlinear Control Applied to a Multicell AFE Rectifier.

The use of controlled power converters has been extended for high power applications, stacking off-the-shelve semiconductors, and allowing the implementation of, among others, AC drives for medium voltages of 2.3 kV to 13.8 kV.

A review on quantum computing and deep learning algorithms and their applications.

In this paper, we describe a review concerning the Quantum Computing (QC) and Deep Learning (DL) areas and their applications in Computational Intelligence (CI). Quantum algorithms (QAs), engage the rules of quantum mechanics to solve problems using quantum information, where the quantum information is concerning the state of a quantum system, which can be manipulated using quantum information algorithms and other processing techniques. Nowadays, many QAs have been proposed, whose general conclusion is that using the effects of quantum mechanics results in a significant speedup (exponential, polynomial, super polynomial) over the traditional algorithms.

Application of a Control Scheme Based on Predictive and Linear Strategy for Improved Transient State and Steady-State Performance in a Single-Phase Quasi-Z-Source Inverter.

Z and quasi-Z-source inverters (Z/qZSI) have a nonlinear impedance network on their dc side, which allows the system to behave as a buck-boost converter in their outputs. The challenges derived from the qZSI topology include (a) the control of the voltage and current on its nonlinear impedance network, (b) the dynamic coupling between the ac and dc variables, and (c) the fact that a unique set of switches are used to manage the power at dc and ac side of the system. In this work, a control scheme that combines a PWM linear control strategy and a strategy based on finite control state model predictive control (FCS-MPC) is proposed.

Long-term longitudinal evaluation of the prevalence of SARS-CoV-2 antibodies in healthcare and university workers.

Asymptomatic and pauci-symptomatic cases contribute to underestimating the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Moreover, we have few studies available on the longitudinal follow-up of SARS-CoV-2 antibodies after natural infection. We tested staff members of a Belgian tertiary academic hospital for SARS-CoV-2 IgG, IgM, and IgA antibodies.

HPV infection alters vaginal microbiome through down-regulating host mucosal innate peptides used by Lactobacilli as amino acid sources.

Despite the high prevalence of both cervico-vaginal human papillomavirus (HPV) infection and bacterial vaginosis (BV) worldwide, their causal relationship remains unclear. While BV has been presumed to be a risk factor for HPV acquisition and related carcinogenesis for a long time, here, supported by both a large retrospective follow-up study (n = 6,085) and extensive in vivo data using the K14-HPV16 transgenic mouse model, we report a novel blueprint in which the opposite association also exists. Mechanistically, by interacting with several core members (NEMO, CK1 and β-TrCP) of both NF-κB and Wnt/β-catenin signaling pathways, we show that HPV E7 oncoprotein greatly inhibits host defense peptide expression.

Fuzzy dynamic parameter adaptation in the bird swarm algorithm for neural network optimization.

Fuzzy dynamic parameter adaptation has proven to be of great help when it is implemented in bio-inspired algorithms for optimization in different application areas, such as control, mathematical functions, classification, among others. One of the main contributions of this work is the proposed improvement of the Bird Swarm algorithm using a Fuzzy System approach, and we called this improvement the Fuzzy Bird Swarm Algorithm. Furthermore, we use a set of complex Benchmark Functions of the Congress on Evolutionary Computation Competition 2017 to compare the results between the original algorithm and the proposed improvement of the algorithm.

Evaluation of the Revogene® GBS DS assay performance for the intrapartum screening of group B streptococcus in comparison with intrapartum culture.

Prevention of perinatal Group B Streptococcus (GBS) transmission is crucial in our effort to prevent Early-onset GBS disease. Here, we established the performance of the Revogene GBS DS assay for the detection of group B streptococcus on intrapartum vaginal samples in a laboratory environment using a prospective noninterventional study design. Intrapartum vaginal swabs were enriched using a selective culture method which served as study reference method.

A new fuzzy fractal control approach of non-linear dynamic systems: The case of controlling the COVID-19 pandemics.

This article is presenting a first attempt on a proposed fuzzy fractal control method for efficiently controlling nonlinear dynamic systems. The main goal is to combine the main advantages of fractal theoretical concepts and fuzzy logic theory for achieving efficient control of nonlinear dynamic systems. The concept coming from Fractal theory, known as the fractal dimension, can be utilized to measure the complexity of the dynamic behavior of a non-linear plant.

A Novel Method for a COVID-19 Classification of Countries Based on an Intelligent Fuzzy Fractal Approach.

We outline in this article a hybrid intelligent fuzzy fractal approach for classification of countries based on a mixture of fractal theoretical concepts and fuzzy logic mathematical constructs. The mathematical definition of the fractal dimension provides a way to estimate the complexity of the non-linear dynamic behavior exhibited by the time series of the countries. Fuzzy logic offers a way to represent and handle the inherent uncertainty of the classification problem.

Optimization using the firefly algorithm of ensemble neural networks with type-2 fuzzy integration for COVID-19 time series prediction.

In this paper, the latest global COVID-19 pandemic prediction is addressed. Each country worldwide has faced this pandemic differently, reflected in its statistical number of confirmed and death cases. Predicting the number of confirmed and death cases could allow us to know the future number of cases and provide each country with the necessary information to make decisions based on the predictions.

A new prediction approach of the COVID-19 virus pandemic behavior with a hybrid ensemble modular nonlinear autoregressive neural network.

We describe in this paper an approach for predicting the COVID-19 time series in the world using a hybrid ensemble modular neural network, which combines nonlinear autoregressive neural networks. At the level of the modular neural network, which is formed with several modules (ensembles in this case), the modules are designed to be efficient predictors for each country. In this case, an integrator is used to combine the outputs of the modules, in this way achieving the goal of predicting a set of countries.

[The COVID-19 breaker : PCR to the rescue !].

Chronicle of a crisis management at the Clinical Microbiology Laboratory of CHU Liège The SARS-CoV-2 outbreak in December 2019 in China and its expansion across the world and Europe have requested the participation of clinical laboratories as major players in the diagnosis of COVID-19, to perform PCR tests mainly on nasopharyngeal swabs. In Belgium, the first confirmed COVID-19 patient was diagnosed in early February, the first of many, especially travelers returning from winter sports. In order to meet the ever-increasing demands for testing, the Clinical Microbiology Laboratory of the CHU of Liege had to adapt to this situation: firstly, by developing manual PCR tests and then automated solutions, permitting to increase the number of analyzes by ensuring a short turnaround time of results.