Showing papers by "Ghent University published in 2022"
TL;DR: In this paper , a spatial proteogenomic atlas of the healthy and obese human and murine liver combining single-cell CITE-seq, single-nuclei sequencing, spatial transcriptomics, and spatial proteomics is presented.
191 citations
TL;DR: The Post-hospitalisation COVID-19 study (PHOSP-COVID) as mentioned in this paper is a prospective, longitudinal cohort study recruiting adults (aged ≥18 years) discharged from hospital with COVID19 across the UK.
118 citations
TL;DR: Insect cytochrome P450 monooxygenases (P450s) perform a variety of important physiological functions, but it is their role in the detoxification of xenobiotics, such as natural and synthetic insecticides, that is the topic of this review as mentioned in this paper.
Abstract: Insect cytochrome P450 monooxygenases (P450s) perform a variety of important physiological functions, but it is their role in the detoxification of xenobiotics, such as natural and synthetic insecticides, that is the topic of this review. Recent advances in insect genomics and postgenomic functional approaches have provided an unprecedented opportunity to understand the evolution of insect P450s and their role in insect toxicology. These approaches have also been harnessed to provide new insights into the genomic alterations that lead to insecticide resistance, the mechanisms by which P450s are regulated, and the functional determinants of P450-mediated insecticide resistance. In parallel, an emerging body of work on the role of P450s in defining the sensitivity of beneficial insects to insecticides has been developed. The knowledge gained from these studies has applications for the management of P450-mediated resistance in insect pests and can be leveraged to safeguard the health of important beneficial insects. Expected final online publication date for the Annual Review of Entomology, Volume 67 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
69 citations
TL;DR: In this paper , an inducible model of ferroptosis was presented, distinguishing three phases in the process, i.e., initial, intermediate and terminal, associated with lipid peroxidation and ATP release, respectively.
Abstract: Immunogenic cell death significantly contributes to the success of anti-cancer therapies, but immunogenicity of different cell death modalities widely varies. Ferroptosis, a form of cell death that is characterized by iron accumulation and lipid peroxidation, has not yet been fully evaluated from this perspective. Here we present an inducible model of ferroptosis, distinguishing three phases in the process-'initial' associated with lipid peroxidation, 'intermediate' correlated with ATP release and 'terminal' recognized by HMGB1 release and loss of plasma membrane integrity-that serves as tool to study immune cell responses to ferroptotic cancer cells. Co-culturing ferroptotic cancer cells with dendritic cells (DC), reveals that 'initial' ferroptotic cells decrease maturation of DC, are poorly engulfed, and dampen antigen cross-presentation. DC loaded with ferroptotic, in contrast to necroptotic, cancer cells fail to protect against tumor growth. Adding ferroptotic cancer cells to immunogenic apoptotic cells dramatically reduces their prophylactic vaccination potential. Our study thus shows that ferroptosis negatively impacts antigen presenting cells and hence the adaptive immune response, which might hinder therapeutic applications of ferroptosis induction.
51 citations
TL;DR: In this article, post-consumer plastic packaging waste fractions, namely mixed polyolefins (MPO), polyethylene (PE), and polypropylene (PP), were processed in a continuous pilot-scale pyrolysis unit and the pyrolys oils subsequently characterized using advanced analytical techniques such as two-dimensional gas chromatography.
50 citations
TL;DR: In this paper , post-consumer plastic packaging waste fractions, namely mixed polyolefins (MPO), polyethylene (PE), and polypropylene (PP), were processed in a continuous pilot-scale pyrolysis unit and the pyrolys oils subsequently characterized using advanced analytical techniques such as two-dimensional gas chromatography.
50 citations
TL;DR: In this paper, the authors provide a comprehensive understanding of Se biogeochemistry in the soil-plant-human system, including strategies for biofortification in Se-deficient areas, factors affecting Se uptake and transport by plants, metabolic pathways of Se in the human body, and interactions between Se and other trace elements in plant and animals, in particular, the detoxification of heavy metals by Se.
50 citations
TL;DR: In this paper, a review of MOFs' features as semiconductor photocatalysts and various means of improving their light-harvesting, charge separation and CO2 adsorption capacity is presented.
43 citations
Hamburg University of Applied Sciences1, Manchester Metropolitan University2, École Normale Supérieure3, University of Chicago4, Sokoine University of Agriculture5, University of Dammam6, Czech University of Life Sciences Prague7, Ghent University8, University of the Sunshine Coast9, University of Cape Town10, Council of Scientific and Industrial Research11
TL;DR: The most frequently identified actors responding to water scarcity include individuals or households (32%), local government (15%), and national government ( 15%), while the most common types of response are behavioural and cultural (30%), technological and infrastructural (27%), ecosystem-based (25%), and institutional (18%). Most responses target low-income communities (31%), women (20%), and indigenous communities (13%), but very few studies target migrants, ethnic minorities or those living with disabilities as discussed by the authors.
42 citations
TL;DR: In this article , an inverse problem for crack identification in two-dimensional structures using eXtend Finite Element Method (XFEM) associated with original Grey Wolf Optimization (GWO) and improved GWO using PSO (IGWO).
41 citations
TL;DR: In this paper, the effect of using natural and recycled coarse aggregates in designing 3D printable concrete was examined using a dynamic shear rheometer, and it was observed that the addition of coarse aggregate significantly decreased the yield stress and marginally lowered the plastic viscosity.
Abstract: In the current study, we examine the effect of using natural and recycled coarse aggregates in designing 3D printable concrete. We assessed the rheological behaviourusing a dynamic shear rheometer, and it was observed that the addition of coarse aggregates significantly decreased the yield stress and marginally lowered the plastic viscosity. This was attributed to the increase in the paste and water film thickness with the addition of larger aggregates. Therefore, a reduction in the superplasticizer dosage is required to obtain coarse aggregate mixtures with similar yield stress and buildability to the control mixture. The mechanical properties were evaluated by using beam and cube samples cut out from printed wall elements. A marginal decrease in compression and flexural strength was observed for both the mixtures with natural and recycled coarse aggregates. The total and autogenous shrinkage assessment was performed using mould cast prismatic specimens, while the shrinkage cracking potential was evaluated using the restrained ring test. The coarse aggregate mixtures showed lower total and autogenous shrinkage. Notably, the addition of the saturated recycled aggregates significantly lowered the autogenous shrinkage, possibly due to internal curing. As a result, a relatively lower strain rate factor and slower development of tensile stresses occurred in the restrained shrinkage test, increasing the cracking age for the coarse aggregate mixtures. The current study, therefore, shows good potential for using natural and recycled coarse aggregates in 3D printable concrete.
TL;DR: In this article , a series of experiments were conducted to systematically and quantitatively explore the effects of control factors on the early age properties of slag and fly ash-based alkali-activated paste (BFS/FA-AAP).
Abstract: In this paper, a series of experiments were conducted to systematically and quantitively explore the effects of control factors on the early age properties, i.e., workability and strength of slag and fly ash-based alkali-activated paste (BFS/FA-AAP). The control factors on the workability (flowability and setting time) of BFS/FA-AAP include the Na2O/b ratio, the SiO2/Na2O ratio, the w/b ratio, and the BFS/b ratio. The control factors on strength (compressive strength and flexural strength) of BFS/FA-AAP further also include the curing condition and the curing age. The results show that a higher BFS/b ratio and Na2O/b ratio could increase the strength while decreasing the workability. A higher w/b ratio could increase the workability while slightly decreasing the strength. Higher SiO2/Na2O ratio increases both strength and workability. Despite that, higher Na2O/b ratio and SiO2/Na2O ratio could hinder the strength development. Sealed curing condition is proved to be a simple but efficient way to assure the steady strength development of BFS/FA-AAP. Although the strength of BFS/FA-AAP could generally stabilize after 90 days, the strength development rate varies with different mix proportions. In addition, a general methodology have been proposed to predict the compressive strength of BFS/FA-AAP and verified with experiments. Finally, a mix design table is proposed for the preliminary design of BFS/FA-AAP according to the principle of satisfying early age requirements.
TL;DR: In this paper, a convolutional neural network based deep learning architecture is proposed to automatically extract the discrete damage features from the scalogram images and use them to classify damage-source regions in the composite panel.
Abstract: Structural health monitoring for lightweight complex composite structures is being investigated in this paper with a data-driven deep learning approach to facilitate automated learning of the map of transformed signal features to damage classes. Towards this, a series of acoustic emission (AE) based laboratory experiments have been carried out on a composite sample using a piezoelectric AE sensor network. The registered time-domain AE signals from the assigned sensor networks on the composite panel are processed with the continuous wavelet transform to extract time-frequency scalograms. A convolutional neural network based deep learning architecture is proposed to automatically extract the discrete damage features from the scalogram images and use them to classify damage-source regions in the composite panel. The proposed deep-learning approach has shown an effective damage monitoring potential with high training, validation and test accuracy for unseen datasets as well as for entirely new neighboring damage datasets. Further, the proposed network is trained, validated and tested only for the peak-signal data extracted from the raw AE data. The application of peak-signal scalogram data has shown a significant improvement in damage-source classification performance with high training, validation and test accuracy.
TL;DR: It was proposed that for amorphous catalysts, the oxygen vacancy helped the chemisorption of toluene, and adjacent Mn reacted as the main active site for the ozonation process, and the redox pair of Cu+/Mn4+ and Cu2+/(Mn3+, Mn2+) in the spinel phase plays an important role in the generation of oxygen vacancies for O3 decomposition.
TL;DR: In this article, a tandem micro-pyrolyzer coupled with comprehensive two-dimensional gas chromatography and FID/ToF-MS detectors was utilized to study the performance of industrial formulations of steam-treated FCC catalysts and HZSM-5 additives for the in-line catalytic upgrading of polyolefin pyrolysis products towards light olefins and aromatics in two steps.
TL;DR: This work introduces a machine learning based technique that relies on satellite weather data and low-frequency inverter measurements for accurate fault diagnosis of PV systems, and demonstrates that this approach is sensitive to faults with a severity as small as 5 %.
TL;DR: In this paper, the authors address challenges and opportunities, as well as facilitation strategies needed to progress the complete re-utilization of waste concrete as a valuable resource for creating sustainable future infrastructure.
Abstract: Global demand for buildings and infrastructure is extremely high as provision of shelter, sanitation and healthcare are paramount to safeguard the world's growing population. Concrete is a preferred construction material to meet this demand, but its production is leading to overexploitation of natural gravel and sand, causing an environmental crisis in regions where these materials are extracted unsustainably. Waste concrete is available globally, particularly in regions with fast growth of the built environment, and those struck by coordinated attacks, earthquakes or severe weather events. Waste concrete has mainly been used for producing recycled aggregates; however, its full recycling is still not practiced. Alternative uses include applications as fine recycled aggregates, supplementary cementitious materials, filler, and feedstocks for clinker production. These technologies still face challenges concerning their adoption and eco-efficiency. Restricted knowledge and operational barriers have also prevented implementation of beneficiation technologies for complete re-recycling of waste concretes, particularly the fine fractions produced during crushing. Despite these issues, it is recognised that the complete utilization of waste concrete offers unique opportunities for supply chain security, reducing natural resources consumption and enabling to move towards a Circular Economy. Harmonizing current practices for the treatment of waste concrete and the by-products generated during their processing, is a first step toward policy and standards development to enable their widespread use. This critical discussion addresses challenges and opportunities, as well as facilitation strategies needed to progress the complete re-utilization of waste concrete as a valuable resource for creating sustainable future infrastructure.
TL;DR: In this paper, the authors investigated whether and how nanomaterials could directly facilitate the dissemination of AMR through horizontal gene transfer, and they found that commonly-used nanoparticles (NPs) (Ag, CuO and ZnO NPs) and their ion forms (Ag+, Cu2+and Zn2+) at realistic concentrations within aquatic environments can significantly promote the transformation of extracellular antibiotic resistance genes in Acinetobacter baylyi ADP1 by a factor of 11.0-folds, which is comparable to the effects of antibiotics.
TL;DR: In this paper , a comprehensive HT-GC × GC FID/MS enables reliable detection and quantification of RCF lignin monomers, dimers and trimers.
TL;DR: In this article, all-aqueous mangosteen-like core-shell multicompartmental microparticles were created by an oil-free gas-shearing fabrication approach.
TL;DR: In this paper, the effects of silica fume and sodium silicate-based activators (SFA and SSA, respectively) with different SiO2/Na2O values on the setting behavior, rheological, mechanical, and microstructural properties of alkali-activated slag cement (AASC) were investigated.
Abstract: The effects of silica fume and sodium silicate-based activators (SFA and SSA, respectively) with different Ms (SiO2/Na2O) values on the setting behavior, rheological, mechanical, and microstructural properties of alkali-activated slag cement (AASC) were investigated. Setting time test results showed that the setting time of AASCs activated by SFA prolonged significantly with an increase of Ms value opposite to SSA activation case. From the rheological point of view, SFA-activated mixtures exhibited a slower structural build-up in the early stage and better workability retention than SSA-activated mixtures. In addition, SFA mixtures showed lower drying shrinkage and slightly higher mechanical properties as compared to SSA mixtures. Microstructure analysis revealed that the mixture produced by SFA with Ms value of 1.2 had less micro-cracks and a well-packed microstructure as compared to the mixtures produced by SSA. The overall evaluation of the test results revealed that SFA could be more economical and sustainable alternative to SSA with its lower cost, much lower CO2 emissions, and more favorable engineering properties.
TL;DR: In this article , the effects of silica fume and sodium silicate-based activators (SFA and SSA, respectively) with different SiO2/Na2O values on the setting behavior, rheological, mechanical, and microstructural properties of alkali-activated slag cement (AASC) were investigated.
Abstract: The effects of silica fume and sodium silicate-based activators (SFA and SSA, respectively) with different Ms (SiO2/Na2O) values on the setting behavior, rheological, mechanical, and microstructural properties of alkali-activated slag cement (AASC) were investigated. Setting time test results showed that the setting time of AASCs activated by SFA prolonged significantly with an increase of Ms value opposite to SSA activation case. From the rheological point of view, SFA-activated mixtures exhibited a slower structural build-up in the early stage and better workability retention than SSA-activated mixtures. In addition, SFA mixtures showed lower drying shrinkage and slightly higher mechanical properties as compared to SSA mixtures. Microstructure analysis revealed that the mixture produced by SFA with Ms value of 1.2 had less micro-cracks and a well-packed microstructure as compared to the mixtures produced by SSA. The overall evaluation of the test results revealed that SFA could be more economical and sustainable alternative to SSA with its lower cost, much lower CO2 emissions, and more favorable engineering properties.
TL;DR: In this article , a tandem micro-pyrolyzer coupled with comprehensive two-dimensional gas chromatography and FID/ToF-MS detectors was utilized to study the performance of industrial formulations of steam-treated FCC catalysts and HZSM-5 additives for the in-line catalytic upgrading of polyolefin pyrolysis products towards light olefins and aromatics in two steps.
TL;DR: In this article , a WOA-ANN hybrid model was proposed for predicting the crack length based on different input values, i.e. strains, stresses, and displacements, to test the accuracy of the presented technique.
TL;DR: In this paper , a literature review on the integration of LCA, EERA, and Ecosystem Services Assessment (ESA) is presented, where three categories of integration are distinguished: post-analysis, integration through the combination of results, and integration through complementation of a driving method.
TL;DR: In this article, the use of covalent organic frameworks (COFs) as fluorescence sensors and adsorbents for the detection and adsorption of organic arsenic from water has been investigated for the first time.
TL;DR: In this paper, social scientists across disciplines have been researching how value is extracted and governed in the reproductive bioeconomy, which broadly refers to the various ways re-ranking is used.
Abstract: Over the last two decades, social scientists across disciplines have been researching how value is extracted and governed in the reproductive bioeconomy, which broadly refers to the various ways re...
TL;DR: In this paper, the authors evaluated four unsupervised machine learning methods on two recent datasets and then defined their generalization strength using a novel inter-dataset evaluation strategy estimating their adaptability.
Abstract: Through the ongoing digitization of the world, the number of connected devices is continuously growing without any foreseen decline in the near future. In particular, these devices increasingly include critical systems such as power grids and medical institutions, possibly causing tremendous consequences in the case of a successful cybersecurity attack. A network intrusion detection system (NIDS) is one of the main components to detect ongoing attacks by differentiating normal from malicious traffic. Anomaly-based NIDS, more specifically unsupervised methods previously proved promising for their ability to detect known as well as zero-day attacks without the need for a labeled dataset. Despite decades of development by researchers, anomaly-based NIDS are only rarely employed in real-world applications, most possibly due to the lack of generalization power of the proposed models. This article first evaluates four unsupervised machine learning methods on two recent datasets and then defines their generalization strength using a novel inter-dataset evaluation strategy estimating their adaptability. Results show that all models can present high classification scores on an individual dataset but fail to directly transfer those to a second unseen but related dataset. Specifically, the accuracy dropped on average 25.63% in an inter-dataset setting compared to the conventional evaluation approach. This generalization challenge can be observed and tackled in future research with the help of the proposed evaluation strategy in this paper.
Sungkyunkwan University1, University of Jinan2, Advanced Institute of Convergence Technology3, Korea University4, Huazhong University of Science and Technology5, Ghent University6, National Yunlin University of Science and Technology7, National Chin-Yi University of Technology8, National Cheng Kung University9, Tunghai University10, Xi'an Jiaotong University11, Fudan University12
TL;DR: In this article, the co-liquefaction behavior of various biomass feedstocks including lignocellulose, organic solid waste and algae is investigated in detail, and the influences of the essential operation parameters including solvent types, catalyst types, reaction temperature and time, and mixing ratio of different biomasses on co-luquefaction behaviour are also evaluated in detail.
Abstract: Liquefaction is an attractive technology for converting biomass into bio-oil without the requirement for drying feedstock, and the process can be conducted at relatively low temperatures. In the practical application, the treated biomass feedstocks are composed of a mixture of agricultural waste, forestry waste and some organic solid waste. The utilization of co-liquefaction technology is suitable for biomass as it can fully utilize different types of feedstocks and enhance the liquefaction degree of each feedstock. During the co-liquefaction of these blending biomass feedstocks, the individual biomass species can degrade according to their own reaction network that is governed by the unique structural compositions. Furthermore, the reaction intermediates from the degradation of different biomasses can potentially interact with each other. This will affect the reaction characteristics and alter the chemical constituents and properties of the bio-oil produced. The understanding of interaction for the blending biomasses during the co-liquefaction process is of significance for tuning the chemical species and yield of the resulting bio-oil. Thus, this review work focuses on the co-liquefaction behavior of the various biomass feedstocks including lignocellulose, organic solid waste and algae. The influences of the essential operation parameters including solvent types, catalyst types, reaction temperature and time, and the mixing ratio of different biomasses on co-liquefaction behavior are also evaluated in detail. The choice of the proper reaction parameters is dependent on the structural characteristics of mixed feedstocks. Additionally, the co-liquefaction impact on the composition and formation mechanism of bio-oils are investigated.
TL;DR: In this article, hollow fiber membrane contactor (HFMC) and two vacuum thermal stripping processes, a rotary evaporator (VTS) and multi-component system (MVTS), were compared for their ability to recover ammonia (NH3) from ion exchange (IEX) regeneration brines.